delta-io/delta

Executive summary

delta-io/delta falls short of our standard for production, held back most by its Code Health lens, the quality of the code itself. It scores 66 out of 100 and is rated Adequate, and 15 of its 25 critical findings are security problems.

Code Health, at 62, is the weakest lens, level with Production Readiness, and counts most in the score. The best first step is declaring which values may be missing, worth about 4 points. Documenting the recovery plan comes next, worth about 2 points. Raising Code Health to 70 would lift the score to about 68.

Four known security holes in the packages the code depends on can be used by attackers. Four weaknesses in the code could be used by an attacker, and eight parts of the code are no longer understood by anyone working on it. Updating the vulnerable packages, fixing the weaknesses the scanner points to and having someone learn the forgotten files would close these risks. Passing outside input through environment variables would fix the three pipeline steps that put outside input straight into a shell command, and reading outside data into plain values would deal with the two places where outside data is turned straight into objects. The loop of parts of the code that depend on each other needs breaking by moving the shared parts into a project of their own.

The product code is 277,583 lines, about €750,000 to rebuild.

Code Health 62 Adequate, capped by Nullable reference types Architecture 87 Adequate, capped by Project Cohesion Maturity 71 Strong Production Readiness 62 Adequate Security and Compliance 77 Adequate, capped by Static Analysis (SAST) Performance 78 Strong

A lens is capped at Adequate while one of its dimensions scores below 4 out of 10, however well the rest of the lens does. That way a serious problem in one place always shows in the lens's rating.

How the score is built: what each lens counts for The lenses don't count equally. The weakest lens counts most, the next weakest a little less, and so on, so a weak area pulls the score down instead of being averaged away. In the bar below, each part's width shows how much that lens counts and its colour shows its rating. Improving the widest part moves the score most, and as that lens improves, it counts for less, because another lens becomes the weakest.

Code Health 62 · counts for 46%Production Readiness 62 · counts for 25%Maturity 71 · counts for 14%Security and Compliance 77 · counts for 8%Performance 78 · counts for 4%Architecture 87 · counts for 2%

If Code Health rose from 62 to 70, the lowest score rated Strong, the score would rise from 66 to about 68.

Code composition: what the lines of code are

Product code 44%Tests 56%

New since the last survey: 118 findings

These 118 critical or serious findings weren't in the previous survey, on 12 October 2026. The first 100 are listed here, and the findings file in the download package lists them all.

Cyclomatic Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Cyclomatic Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cyclomatic 30) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Cyclomatic Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cyclomatic 25) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cyclomatic Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cyclomatic 23) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java
Cyclomatic Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cyclomatic 21) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cyclomatic Complexity · SchemaUtils.reportDifferencesByCategory (cyclomatic 19) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala
Cyclomatic Complexity · SparkRowToKernelRow.sparkValueToKernel (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java
Cyclomatic Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java
Cyclomatic Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java
Cyclomatic Complexity · KernelRowToSparkRow.toSparkValue (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java
Cyclomatic Complexity · DeltaInsertCastSupport.addCastToColumn (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/DeltaInsertCastSupport.scala
Cyclomatic Complexity · PartitionUtils.convertRowValueToKernelLiteral (cyclomatic 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
Cognitive Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cognitive 107) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cognitive 56) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cognitive 45) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java
Cognitive Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cognitive 38) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cognitive 38) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · SchemaUtils.reportDifferencesByCategory (cognitive 27) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala
Cognitive Complexity · SparkRowToKernelRow.sparkValueToKernel (cognitive 24) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java
Cognitive Complexity · DeltaV2MicroBatchStream.applyPerCommitCDCAdmission (cognitive 20) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · AddFile.withoutTightBoundStatsPreservingPrecision (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala
Cognitive Complexity · DeltaV2MicroBatchStream.getCommitsFromRange (cognitive 19) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · CDCReaderBase.checkBatchCdfReadSchemaIncompatibility (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReaderBase.scala
Cognitive Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cognitive 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java
Cognitive Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cognitive 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java
Cognitive Complexity · KernelRowToSparkRow.equals (cognitive 17) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java
Cognitive Complexity · KernelRowToSparkRow.toSparkValue (cognitive 17) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java
Cognitive Complexity · PartitionUtils.convertRowValueToKernelLiteral (cognitive 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.checkReadIncompatibleSchemaChangeOnStreamStartOnce (cognitive 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
God Classes · ClassTooLong: DeltaV2MicroBatchStream spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
God Classes · FileTooLong: read/DeltaV2MicroBatchStream.java spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
God Classes · MethodTooLong: ExpressionUtils.dsv2PredicateToCatalystExpression spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
God Classes · TooManyMethods: DeltaV2MicroBatchStream spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
God Classes · ClassTooLong: PartitionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
God Classes · FileTooLong: utils/PartitionUtils.java spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
God Classes · TooManyMethods: DeltaV2Scan spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2Scan.java
God Classes · MethodTooLong: DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
God Classes · TooManyMethods: PartitionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
God Classes · ClassTooLong: ExpressionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
God Classes · FileTooLong: sources/DeltaSourceMetadataEvolutionSupport.scala spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceMetadataEvolutionSupport.scala
Code Duplication · Duplicated block (58 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java
Code Duplication · Duplicated block (16 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (14–15 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
Code Duplication · Duplicated block (12–14 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Code Duplication · Duplicated block (10 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java
Code Duplication · Duplicated block (9 lines × 3) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java
Code Duplication · Duplicated block (8 lines × 7) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (7 lines × 3) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (7 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/cdc/CDCReadFunction.java
Code Duplication · Duplicated block (6 lines × 10) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (6 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2Write.java
Code Duplication · Duplicated block (5 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Code Duplication · Duplicated block (5 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java
Churn × Complexity Hotspots · Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala
Churn × Complexity Hotspots · Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala
Churn × Complexity Hotspots · Hotspot: spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/V2DDLTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStreamCDCTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/read/SparkGoldenTableTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/test/java/org/apache/spark/sql/delta/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/main/scala/org/apache/spark/sql/delta/v2/read/KernelStreamingBackend.scala
Explicit Debt · TodoComment spark/v2/src/main/scala/org/apache/spark/sql/delta/v2/read/ProtocolMetadataAdapterV2.scala
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2-4.3/org/apache/spark/sql/delta/v2/read/changelog/DeltaV2Changelog.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2-4.3/org/apache/spark/sql/delta/v2/read/changelog/DeltaV2Changelog.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2-4.3/org/apache/spark/sql/delta/v2/read/changelog/DeltaV2ChangelogBatch.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2-4.3/org/apache/spark/sql/delta/v2/read/changelog/DeltaV2ChangelogScan.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2DataWriter.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2WriteBuilder.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2WriteBuilder.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/snapshot/unitycatalog/UCUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2Scan.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2Scan.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2Scan.java
Explicit Debt · TodoComment spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java
Explicit Debt · TodoComment spark/unitycatalog/src/test/java/io/sparkuctest/UnityCatalogSupport.java
Explicit Debt · HackComment spark/src/test/scala/org/apache/spark/sql/delta/test/CustomCatalogs.scala

Watchdog compares every finding with the previous survey's. A finding that has only moved to another line in the same file counts as the same finding, so only new findings appear here. Advisory notes from the AI model are left out, because the model words them afresh in every survey.

Fixed since the last survey: 107 findings

These 107 critical or serious findings were in the previous survey, on 12 October 2026, and are gone from this one. The first 100 are listed here.

Cyclomatic Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Cyclomatic Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cyclomatic 30) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Cyclomatic Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cyclomatic 23) spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Cyclomatic Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cyclomatic 23) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cyclomatic Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cyclomatic 21) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cyclomatic Complexity · SparkRowToKernelRow.sparkValueToKernel (cyclomatic 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SparkRowToKernelRow.java
Cyclomatic Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cyclomatic 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SchemaUtils.java
Cyclomatic Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cyclomatic 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SchemaUtils.java
Cyclomatic Complexity · KernelRowToSparkRow.toSparkValue (cyclomatic 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/KernelRowToSparkRow.java
Cyclomatic Complexity · SchemaUtils.reportDifferences (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala
Cyclomatic Complexity · PartitionUtils.convertRowValueToKernelLiteral (cyclomatic 16) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Cognitive Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cognitive 107) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cognitive 54) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cognitive 45) spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Cognitive Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cognitive 38) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cognitive 38) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · SparkRowToKernelRow.sparkValueToKernel (cognitive 24) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SparkRowToKernelRow.java
Cognitive Complexity · SchemaUtils.reportDifferences (cognitive 22) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala
Cognitive Complexity · DeltaImplicitCast.apply (cognitive 20) spark/src/main/scala/org/apache/spark/sql/delta/DeltaImplicitCast.scala
Cognitive Complexity · DeltaV2MicroBatchStream.applyPerCommitCDCAdmission (cognitive 20) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · DeltaV2MicroBatchStream.getCommitsFromRange (cognitive 19) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Cognitive Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cognitive 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SchemaUtils.java
Cognitive Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cognitive 18) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SchemaUtils.java
Cognitive Complexity · KernelRowToSparkRow.equals (cognitive 17) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/KernelRowToSparkRow.java
Cognitive Complexity · KernelRowToSparkRow.toSparkValue (cognitive 17) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/KernelRowToSparkRow.java
Cognitive Complexity · PartitionUtils.convertRowValueToKernelLiteral (cognitive 16) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Cognitive Complexity · DeltaV2MicroBatchStream.checkReadIncompatibleSchemaChangeOnStreamStartOnce (cognitive 16) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
God Classes · ClassTooLong: DeltaV2MicroBatchStream spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
God Classes · FileTooLong: read/DeltaV2MicroBatchStream.java spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
God Classes · MethodTooLong: ExpressionUtils.dsv2PredicateToCatalystExpression spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
God Classes · TooManyMethods: DeltaV2MicroBatchStream spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
God Classes · TooManyMethods: DeltaV2Table spark/v2/src/main/java/io/delta/spark/internal/v2/catalog/DeltaV2Table.java
God Classes · TooManyMethods: DeltaV2Scan spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2Scan.java
God Classes · ClassTooLong: PartitionUtils spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
God Classes · MethodTooLong: DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
God Classes · ClassTooLong: ExpressionUtils spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
God Classes · FileTooLong: utils/PartitionUtils.java spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
God Classes · FileTooLong: read/MetadataEvolutionHandler.java spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Code Duplication · Duplicated block (8 lines × 2) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergTransactionUtils.scala
Code Duplication · Duplicated block (58 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/KernelRowToSparkRow.java
Code Duplication · Duplicated block (16 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (14–15 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Code Duplication · Duplicated block (12–14 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Code Duplication · Duplicated block (10 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SchemaUtils.java
Code Duplication · Duplicated block (9 lines × 3) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/StreamingHelper.java
Code Duplication · Duplicated block (8 lines × 7) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (7 lines × 3) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (7 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/read/cdc/CDCReadFunction.java
Code Duplication · Duplicated block (6 lines × 10) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Code Duplication · Duplicated block (6 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2Write.java
Code Duplication · Duplicated block (5 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Code Duplication · Duplicated block (5 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/utils/SparkRowToKernelRow.java
Code Duplication · Duplicated block (5 lines × 2) spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2Scan.java
Cohesion (LCOM4) · Low cohesion: DeltaV2OptimisticTransaction (LCOM4 5) spark/v2/src/main/scala/org/apache/spark/sql/delta/v2/interop/DeltaV2OptimisticTransaction.scala
Churn × Complexity Hotspots · Hotspot: spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Churn × Complexity Hotspots · Hotspot: kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java
Churn × Complexity Hotspots · Hotspot: spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Explicit Debt · TodoComment spark/src/test/scala/org/apache/spark/sql/delta/amt/AMTSingleCommitSuite.scala
Explicit Debt · TodoComment spark/src/test/scala/org/apache/spark/sql/delta/amt/AMTSingleCommitSuite.scala
Explicit Debt · TodoComment spark/src/test/scala/org/apache/spark/sql/delta/amt/AMTCheckpointTestBase.scala
Explicit Debt · TodoComment spark/src/test/scala/org/apache/spark/sql/delta/amt/AMTBackReferenceSuite.scala
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2/io/delta/spark/internal/v2/read/changelog/DeltaV2ChangelogScan.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2/io/delta/spark/internal/v2/read/changelog/DeltaV2ChangelogBatch.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2/io/delta/spark/internal/v2/read/changelog/DeltaV2Changelog.java
Explicit Debt · TodoComment spark/v2/src/main/java-shims/spark-4.2/io/delta/spark/internal/v2/read/changelog/DeltaV2Changelog.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/ProtocolMetadataAdapterV2.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/MetadataEvolutionHandler.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2Scan.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2Scan.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStream.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/snapshot/unitycatalog/UCUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/utils/StreamingHelper.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/utils/PartitionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/utils/ExpressionUtils.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2WriteBuilder.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2WriteBuilder.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2StreamingWrite.java
Explicit Debt · TodoComment spark/v2/src/main/java/io/delta/spark/internal/v2/write/DeltaV2DataWriter.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/V2StreamingReadTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/V2DDLTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/catalog/TestCatalog.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/read/SparkGoldenTableTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStreamTest.java
Explicit Debt · TodoComment spark/v2/src/test/java/io/delta/spark/internal/v2/read/DeltaV2MicroBatchStreamTest.java

Rebuild cost: about €750,000 · Estimate

Cost to rebuild	€250,000 to €1,200,000, for 4,132 to 13,107 hours of work, about 5.1 person-years for 3 to 10 engineers
Difficulty of the problem	Standard, judged from the kind of software and how it is built. Code that solves a harder problem, such as payments or medical bookings, costs more per line to write.
Quality factor	×0.9 at a score of 66. Better code takes more work to write, so the factor is ×1.0 at a score of 70, lower below it and higher above it.
Size	Large: 277,583 lines of product code
What it is not	Not a quotation: nobody has offered to build it for that. Not a valuation: it says nothing about what the business is worth. Not a certified figure: no professional has signed it as one.

How the estimate is made: Watchdog prices the hours a team would need to write this code again, at €60 to €95 an hour. Declarations and boilerplate are priced at a fast rate and logic at a slower one, and the logic is then multiplied by the difficulty of the problem and by the quality factor. The estimate can be about 30% off either way, and it moves most with the hourly rate and the difficulty. For this code, every line is priced as straight logic, which keeps the estimate on the low side.

Top priorities

The three actions that raise the score most for the work they take. The full ranked list is in the Roadmap.

Then pay the assertions down rather than adding to them: each `.nn` is a null the compiler could not rule out — wrap the Java value in `Option(…)` at the boundary, pattern-match on `null` once there, or change the API so the null cannot arrive; an `unsafeNulls` import switches the checking off for everything after it.

Raises the score by about 4 points · Medium effort · Nullable reference types

Document RTO/RPO and a tested restore procedure (a backup config alone isn't disaster recovery).

Raises the score by about 2 points · Medium effort · DR & Backup

Resolve the 8 Orphaned knowledge finding(s) in Knowledge Freshness — start with LogSegment.java, DeltaMergeBuilder.scala, Protocol.java.

Raises the score by about 0.9 points · Low effort · Knowledge Freshness

Diagnosis: what the measurements show together

Each conclusion below combines several dimensions into one point that no single dimension shows, and lists the measurements it rests on.

Where the investment is most exposed · Value at risk

This code would cost about €750,000 to build again, about 5.1 person-years of work. Its weakest lens is Code Health, at 62 (Adequate). Code Health is about how easy the code is to read and change safely, and code that is hard to read is slow and risky to change, so every future change costs more than it should. Because the weakest lens counts most in the score, work on Code Health also moves the score most.

Based on: the rebuild estimate · the Code Health grade · how much each lens counts

What to do: Start with the Code Health actions in Top priorities.

If you do one thing first · First action

On Scala 3, add `-Yexplicit-nulls` to `scalacOptions` so `String` and `String | Null` mean different things, and type each Java API's result as nullable where it can return null; on Scala 2 (or as a first step), enable WartRemover's `Null` wart (`wartremoverErrors += Wart.Null`) or Scalafix's `DisableSyntax.noNulls = true` so the code holds absence in `Option`. Of all the actions in this report, it raises the score most for the work it takes: about 4 points for medium effort. The next survey will show the change in the score.

Based on: the ranked actions in Top priorities, by score gain and effort

Architecture — module dependency graph

Project dependencies, layered top-to-bottom; arrows show direction. Any dashed red edge points upward or sideways, which only happens where the projects form a dependency cycle. A graph without cycles has none.

Architecture: which parts of the code depend on which

The code is divided into modules, groups of code that each handle one part of the product, and a module depends on another when it uses code from it. The table lists the modules both down the side and across the top, in an order where each module should only use modules listed above it. A number in a cell means the module on that row uses the module in that column, and it counts the pairs of building blocks (types) that connect them. The one thing to look for is a mark above the diagonal line. It means two or more modules use each other in a loop (a dependency cycle), so none of them can be changed, tested or released on its own.

241 modules, with 430 dependencies between them. 2 loops run through 55 of the modules, marked above the diagonal.

The table shows the 40 modules with the most connections; 201 more are left out to keep it readable.

Which modules use which. The module on each row uses the module in each column, and the number counts the pairs of types that connect them. A cell above the diagonal is part of a loop.
uses →	1 com.databricks.spark.util	2 org.apache.spark.sql.catalyst.plans.logical	3 org.apache.spark.sql.delta.CheckpointInstance	4 org.apache.spark.sql.delta.constraints.Invariants	5 org.apache.spark.sql.delta.icebergShaded.IcebergTransactionUtils	6 org.apache.spark.sql.delta.logging.DeltaLogKeysBase	7 org.apache.spark.sql.delta.DeltaOperations	8 org.apache.spark.sql.delta.hooks	9 org.apache.spark.sql.delta.icebergShaded.DeltaToIcebergConvert	10 org.apache.spark.sql.delta.schema	11 org.apache.spark.sql.delta.storage	12 org.apache.spark.sql.delta.commands.convert	13 org.apache.spark.sql.delta.sources	14 org.apache.spark.sql.delta.util	15 org.apache.spark.sql.delta.coordinatedcommits	16 org.apache.spark.sql.delta.storage.dv	17 org.apache.spark.sql.delta.v2	18 org.apache.spark.sql.delta.v2.tablemanager	19 org.apache.spark.sql.delta.v2.interop	20 org.apache.spark.sql.delta.constraints	21 org.apache.spark.sql.delta.files	22 org.apache.spark.sql.delta.stats	23 org.apache.spark.sql.delta.metering	24 org.apache.spark.sql.delta.catalog	25 org.apache.spark.sql.delta.deletionvectors	26 org.apache.spark.sql.delta.amt	27 org.apache.spark.sql.delta.actions	28 org.apache.spark.sql.delta.DeltaHistoryManager	29 org.apache.spark.sql.delta.commands.merge	30 org.apache.spark.sql.delta.skipping.clustering	31 org.apache.spark.sql.delta.commands	32 io.delta.tables	33 org.apache.spark.sql.delta
1 com.databricks.spark.util
2 org.apache.spark.sql.catalyst.plans.logical
3 org.apache.spark.sql.delta.CheckpointInstance
4 org.apache.spark.sql.delta.constraints.Invariants
5 org.apache.spark.sql.delta.icebergShaded.IcebergTransactionUtils
6 org.apache.spark.sql.delta.logging.DeltaLogKeysBase
7 org.apache.spark.sql.delta.DeltaOperations																											3
8 org.apache.spark.sql.delta.hooks																							8				5						19
9 org.apache.spark.sql.delta.icebergShaded.DeltaToIcebergConvert														2													1						3
10 org.apache.spark.sql.delta.schema																			1				2				2						6
11 org.apache.spark.sql.delta.storage																							1
12 org.apache.spark.sql.delta.commands.convert									5					3									6				2						10
13 org.apache.spark.sql.delta.sources									2	1	3										1		3				13	2					10
14 org.apache.spark.sql.delta.util	1				1		1	1	1		1	1	1		1								3			1	8	1					11
15 org.apache.spark.sql.delta.coordinatedcommits						2					3			1					6				3				3						7
16 org.apache.spark.sql.delta.storage.dv														3									1		2		1
17 org.apache.spark.sql.delta.v2				3												1							1		1		2
18 org.apache.spark.sql.delta.v2.tablemanager											4						2		6									3					5
19 org.apache.spark.sql.delta.v2.interop	1							1			1				1			1				2				1	9	2					16
20 org.apache.spark.sql.delta.constraints				1															1				1				1						1
21 org.apache.spark.sql.delta.files							1						1	1						1		1	1				17						12
22 org.apache.spark.sql.delta.stats				1					1					1							2		5				10						7
23 org.apache.spark.sql.delta.metering	4													1								1
24 org.apache.spark.sql.delta.catalog	1								2										1			2	3				6						4
25 org.apache.spark.sql.delta.deletionvectors			1													2							1				2
26 org.apache.spark.sql.delta.amt									4													1	3		2		40						15
27 org.apache.spark.sql.delta.actions	1		1			1	1		12														3	1		1							9
28 org.apache.spark.sql.delta.DeltaHistoryManager																											1
29 org.apache.spark.sql.delta.commands.merge		5			1									1									1				3						3
30 org.apache.spark.sql.delta.skipping.clustering									1													1	1				5				1		3
31 org.apache.spark.sql.delta.commands		6			32		9		8	2		5		2		1				1	5		10	21	1		64		7	1			74
32 io.delta.tables					1				1																						1
33 org.apache.spark.sql.delta	3	11	7	11	1		7	3	43	2	8			8	4				4		6	17	49	58		12	216	4			2
34 io.delta.sharing.spark				1		1							2								2	1	2				1						2
35 io.delta.tables.execution					1									1										1							1	2	1
36 org.apache.spark.sql.connect.delta		3							1																						1	1	1
37 org.apache.spark.sql.delta.OptimisticTransactionImpl											1				1				2			1					2						1
38 org.apache.spark.sql.delta.commands.cdc					1											1					1		1		1		6						11
39 org.apache.spark.sql.delta.icebergShaded												2		3									4				8						9
40 org.apache.spark.sql.delta.v2.read													1				2		1			1						1			1		6

Uses a module listed above itPart of a loopThe module itself

At a glance — Code Health · 62% · Adequate · gated by X5 ·

The Good

D3 · Scala God Classes 8.8 D4 · Scala Code Duplication 9.8 D17 · Scala Explicit Debt 9.7 GD1 · Repo Unfinished & placeholder code 10.0 IC1 · Repo Incompleteness & stubs 8.5 X1 · Repo Async correctness 10.0 X12 · Repo Unreachable branch 10.0 X13 · Repo Undrained process stream 10.0 X16 · Repo Unfloored truncation loop 10.0 X18 · Repo Disposal-pattern correctness 7.1 X19 · Repo Unrestored process-global state 10.0 X20 · Repo Mistyped argument guard 10.0 X21 · Repo Side-effecting pattern guard 10.0 X22 · Repo Contradicted release guard 10.0 X25 · Repo Inert configuration knob 10.0 X26 · Repo Unsynchronised callback handoff 10.0 X27 · Repo Collection changed while being enumerated 10.0 X28 · Repo Index access outside its own emptiness guard 10.0 X29 · Repo Per-element action decided by a fixed element 10.0 X3 · Repo Exception handling 7.3 X30 · Repo Support guard that admits what it rejects 10.0 X4 · Repo Structured logging 7.1

The Bad

D1 · Scala Cyclomatic Complexity 5.9 D2 · Scala Cognitive Complexity 5.4 X23 · Repo Unguarded diagnostic materialisation 6.8

The Ugly

X5 · Repo Nullable reference types 2.0

At a glance — Architecture · 87% · Adequate · gated by D26 ·

The Good

D6 · Scala Cohesion (LCOM4) 9.8 D35 · Scala Change Coupling 9.9 AX10 · Repo Code composition 9.9 AX4 · Repo Dependency direction 10.0 AX6 · Repo Interface segregation 10.0

The Bad

D7 · Scala Architectural Integrity 6.0 AX3 · Repo Project dependency cycles 5.8

The Ugly

D5 · Scala Coupling 4.0 D26 · Scala Project Cohesion 3.3

At a glance — Maturity · 71% · Strong ·

The Good

D15 · Scala Churn × Complexity Hotspots 9.8 D16 · Scala Bus Factor 9.1 D19 · Scala Documentation Quality 10.0 D20 · Scala ADR Quality 10.0 D34 · Scala Knowledge Freshness 7.6 M1 · Repo Documentation (README) 7.0 M3 · Repo Folder & project structure 10.0 M4 · Repo Documentation accuracy 10.0

The Ugly

M2 · Repo Architecture documentation 4.0

At a glance — Readiness · 62% · Adequate ·

The Good

D9 · Scala Test Distribution 9.8 D13 · Scala REDACTED Scanning 10.0 D14 · Scala License Compliance 10.0 P1 · Repo CI/CD gates 10.0 P10 · Repo Library API & versioning 10.0 P4 · Repo Deployment & Rollback 7.0 P6 · Repo Release Hygiene 10.0

The Bad

P2 · Repo Observability 5.0 P3 · Repo Security & performance tooling 5.0

The Ugly

P5 · Repo DR & Backup 4.0

At a glance — Security · 77% · Adequate · gated by D29 ·

The Good

D28 · Scala Secrets (history) 9.0 D30 · Scala Dependency Vulnerabilities 7.5 D31 · Scala IaC & Container Security 9.4 D43 · Scala Malicious Dependencies 10.0 D44 · Scala Platform End-of-Life 10.0 S1 · Repo Web-Security Posture 8.0 X14 · Repo Bypassable address classification 10.0 X24 · Repo Document value interpolated into markup unescaped 10.0

The Bad

D36 · Scala Supply-chain Provenance & Signing 5.0

The Ugly

D29 · Scala Static Analysis (SAST) 1.7 X15 · Repo Unvalidated length from an untrusted reader 2.2 X17 · Repo Uncapped recursion over a caller-supplied document 3.5

At a glance — Performance · 78% · Strong ·

The Good

PF1 · Repo Benchmark discipline 8.0 PF3 · Repo Async & latency hygiene 10.0

The Bad

PF2 · Repo Allocation hygiene 6.3

Security & Compliance — OWASP Top-10 mapping

Findings mapped to OWASP categories; the specific CVEs/secrets are in the Security dimension cards below and findings.md (redacted only on the public version of this report).

OWASP category	Findings	Severity
A03:2025 — Software Supply Chain Failures	19	High / Critical
A05:2025 — Injection	10	High / Critical
A02:2025 — Security Misconfiguration	4	High / Critical
A07:2025 — Authentication Failures	2	High / Critical

Roadmap

First, eliminate null-related risks by enabling strict null checking in Scala and refactoring Java boundaries to use Option types instead of unsafe assertions. Second, establish a tested disaster recovery plan with documented RTO and RPO targets, and extend structured logging across all runnable modules to ensure full production observability. Third, automate dependency security by enabling Dependabot or Renovate, and finally, organize architecture decision records under a consistent naming convention in the docs directory for better discoverability.

Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.

Do this	Helps	Effort	Dimension
On Scala 3, add `-Yexplicit-nulls` to `scalacOptions` so `String` and `String \| Null` mean different things, and type each Java API's result as nullable where it can return null; on Scala 2 (or as a first step), enable WartRemover's `Null` wart (`wartremoverErrors += Wart.Null`) or Scalafix's `DisableSyntax.noNulls = true` so the code holds absence in `Option`. Then pay the assertions down rather than adding to them: each `.nn` is a null the compiler could not rule out — wrap the Java value in `Option(…)` at the boundary, pattern-match on `null` once there, or change the API so the null cannot arrive; an `unsafeNulls` import switches the checking off for everything after it.	+3.5 pts	Medium	Nullable reference types
Document RTO/RPO and a tested restore procedure (a backup config alone isn't disaster recovery).	+2.2 pts	Medium	DR & Backup
Resolve the 8 Orphaned knowledge finding(s) in Knowledge Freshness — start with LogSegment.java, DeltaMergeBuilder.scala, Protocol.java.	+0.9 pts	Low	Knowledge Freshness
Extend structured logging to the remaining runnable modules so everything you run is diagnosable in production.	+1.6 pts	Medium	Observability
Enable Dependabot/Renovate or a dependency-review gate.	+1.6 pts	Medium	Security & performance tooling
Move ADRs under docs/adr/ (or docs/adrs/) and name them NNNN-title.md so they're easy to find.	+1.3 pts	Medium	Architecture documentation
Interpolated log message defeats structured logging	+1.0 pts	Medium	Structured logging
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.	+0.9 pts	Medium	Documentation (README)

File quality

Per-file score 0–10 — a quality signature. Of 379 files carrying findings, judged against the Production bar: 0% slop · 54% mixed · 46% near-clean.

File	Score	Band	Worst signal
REDACTED	3.2	Slop	Static Analysis (SAST): High: REDACTED
REDACTED	4.6	Mixed	Static Analysis (SAST): High: REDACTED
REDACTED	5.1	Mixed	Static Analysis (SAST): High: REDACTED
REDACTED	5.1	Mixed	Dependency Vulnerabilities: High CVE: REDACTED
REDACTED	5.8	Mixed	Static Analysis (SAST): High: REDACTED
spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala	6.0	Mixed	Explicit Debt: TodoComment
spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala	6.0	Mixed	Explicit Debt: TodoComment
kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java	6.0	Mixed	Explicit Debt: TodoComment
icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java	6.0	Mixed	Explicit Debt: HackComment
iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala	6.0	Mixed	Explicit Debt: TodoComment
kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java	6.0	Mixed	Explicit Debt: TodoComment
spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala	6.0	Mixed	Explicit Debt: TodoComment
spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala	6.0	Mixed	Explicit Debt: TodoComment
kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java	6.0	Mixed	Explicit Debt: TodoComment
python/delta/connect/tables.py	6.0	Mixed	Explicit Debt: TodoComment
kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnWriters.java	6.0	Mixed	Explicit Debt: TodoComment

How the grades work

Every finding carries one of four grades. Three say how serious it is. The fourth says this survey could not settle it — and it is a grade, not a gap.

Critical — 25

A definite problem that already costs you something and drags the score down: a missing authorisation check, a dependency with a known exploit, a build that does not reproduce. Failure here tends to cause failures elsewhere.

Serious — 904

Likely wrong, but not failing yet. It degrades the codebase over a longer horizon and can cause failures elsewhere — not urgent this week, not something to carry for two years either.

Minor — 252

Recorded, with no effect on how the codebase functions. Present so the survey is complete, not because it needs doing.

Could not be resolved — 13

Something this survey could not settle from the outside, and which could be critical or serious. Either a control was required and no positive evidence of it exists in the repository — a backup job that nothing shows was ever restored from proves nothing about restores — or our own analysis could not run over that part of the tree. This is not a clean result. These are excluded from the score rather than awarded a pass, so the number on the cover neither rewards nor penalises them: if you act on this survey without resolving them, you carry that risk yourself. Each one is named under Limitations.

Methodology & how to trust this report

Watchdog is a deep, periodic assessment — run each sprint, monthly, or quarterly, taking the time to go wider and deeper than a quick check and surfacing in one coherent report what you'd otherwise piece together from a dozen separate tools. It scores deterministically: the same commit yields the same score, every run. 69 of 69 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); none rely on LLM judgement. Overall confidence is 0.9 — the weighted average across measured dimensions; it falls as more of the score leans on LLM-assisted judgement and rises when it's fully tool-backed.

Every figure here is one of three kinds, and we label which: ✓ Measured — a deterministic fact (LoC, complexity, coverage); ~ Modeled — an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; ◐ Advisory — an LLM prose judgement. We never present a modelled estimate as if it were measured. Perfect or absent scores carry their provenance too (ADR-0011): ✓ Tool-verified means the property itself was measured across the surface; ○ Nothing flagged means the probes came back clean — a claim bounded by what a repository can show; ⊘ Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence — absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; ◐ Sampled · advisory marks an LLM verdict over a bounded sample — advisory, never a deterministic measurement.

What we checked — 69 dimensions across the health lenses

D1D2D3D4D5D6D7D9D13D14D15D16D17D19D20D26D28D29D30D31D34D35D36D43D44AX10AX3AX4AX6GD1IC1M1M2M3M4P1P10P2P3P4P5P6PF1PF2PF3S1X1X12X13X14X15X16X17X18X19X20X21X22X23X24X25X26X27X28X29X3X30X4X5

Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.

How to trust any code-health report — three questions

Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 1158 of 1181 do; the remainder are repo-wide signals — a dimension-level measurement, not a single line. (Every path in this report is repo-relative by construction: paths are normalized at the producer and the report is rejected if any rooted path leaks through.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.

This report answers yes to all three. That's the bar to hold any assessment to.

Tools & methods

The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.

Method	Backs	Version	Evaluator
Roslyn static analysis	Complexity, cohesion, coupling, dead code, API surface, layering	5.3.0	✓ deterministic
Native secret scanner	Hardcoded secrets / credentials	1.0.0	✓ deterministic
Watchdog duplication detector (in-process)	Code duplication	1.0.0	✓ deterministic
Coverage (coverlet / dotnet-coverage)	Line & branch coverage	10.0.400	✓ deterministic
NuGet / dotnet	Outdated, vulnerable & deprecated dependencies	10.0.400	✓ deterministic
git / LibGit2Sharp	Churn hotspots, knowledge concentration, history	2.43.0 · 0.31.0	✓ deterministic
gitleaks · semgrep · trivy · checkov	Secrets in history, SAST, CVEs, IaC & container, PII / GDPR	1.86.0 · 0.69.3 · 3.2.533	✓ deterministic
LLM (sampled · advisory)	Documentation quality, ADR conformance, naming — sampled over a bounded sample; advisory, never a deterministic measurement	—	◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 01a176c7-def1-7679-bc11-5644f3b5d0f0.

The exact command behind every deep-scan dimension — tool, version, invocation and retained raw output — is in Appendix B — Reproduction & audit trail.

Run transparency — what happened this run

What ran differently this time — a tool absent, degraded, or that fell back to an estimate. Named openly, not folded silently into the scores. A degraded run also records its exact cause in diagnostics.md.

D8 Code Coverage — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Coverage NOT MEASURED: test source is present (.py, .scala, .java) but the built-in coverage collector has no runner for this repository's ecosystem — so this suite was never executed by it. Not scored — this is a gap in the analyzer's language coverage, not a defect in the repo. To have real coverage read, produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`, or `addSbtPlugin("org.scoverage" % "sbt-scoverage" % "<version>")` in `project/plugins.sbt`, then `sbt clean coverage test coverageReport`, or JaCoCo XML — `mvn jacoco:report` or the Gradle `jacocoTestReport` task) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures. You can widen what we reach: optional: produce a coverage report in a standard format (`coverage run -m pytest` then `coverage xml`, or `addSbtPlugin("org.scoverage" % "sbt-scoverage" % "<version>")` in `project/plugins.sbt`, then `sbt clean coverage test coverageReport`, or JaCoCo XML — `mvn jacoco:report` or the Gradle `jacocoTestReport` task) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures — then the real number is read on the next scan.
D11 Test Reliability — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Test reliability not included — the Scala suite (repository root, 817 test files) did not finish re-running within its budget: the sbt build did not finish re-running within its tier budget.
D12 Dependency Hygiene — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Not scored — 1 Maven/Gradle manifest(s) were read, stating a version for 7 dependency(ies) and leaving 0 to a parent or an imported BOM, but no build resolved the dependency graph, so the outdated signal was not established. NOT a finding that these dependencies are current or healthy.
D14 License Compliance — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. This repository declares an sbt build (REDACTED), but the licence verdict published here was taken over its JVM dependencies. Nothing was read about its sbt dependencies' licensing in either direction, and a clean score on this card must not be read as covering them.
D14 License Compliance — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. This repository declares a Python pyproject.toml/requirements.txt (pip/uv/Poetry), but the licence verdict published here was taken over its JVM dependencies. Nothing was read about its Python dependencies' licensing in either direction, and a clean score on this card must not be read as covering them.
D14 License Compliance — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. This repository declares package.json, but the licence verdict published here was taken over its JVM dependencies. Nothing was read about its npm dependencies' licensing in either direction, and a clean score on this card must not be read as covering them.
D19 Documentation Quality — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. Each ecosystem's manifests (what makes a folder runnable or a published package) need their own proof before D19 judges its units. Until then those folders' READMEs are judged only as documents (boilerplate, structure), never counted as complete.
D19 Documentation Quality — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. This kind did not reach the 95 % precision gate in three adjudicated runs (docs/plans/deterministic-engine/adjudication/D19-sample3-v3.md), so by the pre-registered fallback it publishes no row until a re-measurement shows it does. The candidates are counted here, not reported as findings, and the score does not include them.
D21 Naming Consistency — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. D21's deterministic naming rules are gated on C# first (docs/plans/deterministic-engine.md, P5): each other language is switched on only after its own concept suite and A/B gate pass. Until then its declarations carry no naming verdict this run — this says nothing about whether its names are consistent.
D22 Internal API Consistency — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. D22's deterministic call-shape rules are gated on C# first (docs/plans/deterministic-engine.md, P5): each other language is switched on only after its own concept suite and A/B gate pass. This says nothing about whether that surface is consistent.
D24 Comment Value — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. This check's reader does not cover the language this repository's product is written in, so it had nothing of the product to read. That is a gap in this analyzer's language reach — not a finding about this repository.
D27 Navigability — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Navigability is taken over call sites whose callee resolved. For C# that population includes calls into referenced assemblies; for this language only calls declared inside the repository count, so the abstention threshold reads the repository's use of its standard library as a resolution failure. That is a limit of this analyzer, not a build problem in this repository.
D28 Secrets (history) — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. D28's config-credential rule (WD-SECRET-0002) parses each committed `.json` config as a document and reads credential-named values; `connectors/golden-tables/src/main/resources/golden/124-decimal-decode-bug/_delta_log/00000000000000000000.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000000.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000001.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000002.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000003.json` and 285 more did not parse (JSON5, a template, several concatenated documents), so a credential bound there is UNMEASURED by that rule. gitleaks still scanned the same files as text.
D32 Data Compliance (PII/GDPR) — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. `spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala`, `spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceOffset.scala` produced a parse error, so every rule in this engine's `gdpr.yml` was absent there. That absence is NOT a clean result: these rules detect personal data crossing a boundary into a log sink, a URL or browser storage, and a file that was never parsed cannot report any of the three. The rest of the tree analysed normally and its rows above stand; only these files are unaccounted for. You can widen what we reach: fix the syntax error (or exclude the file deliberately) and re-scan to cover it.
AXR1 Runtime accessibility — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. Render strategy: boot via DockerCompose (REDACTED). compose up failed (exit 18 — an image could not be pulled) — taskmanager2 Pulling taskmanager Pulling jobmanager Pulling jobmanager Error Get "https://registry-1.docker.io/v2/": Forbidden taskmanager Error context canceled taskmanager2 Error context canceled Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the earlier `compose pull` step reported: taskmanager2 Skipped - Image is already being pulled by taskmanager jobmanager Skipped - Image is already being pulled by taskmanager taskmanager Pulling taskmanager Error Get "https://registry-1.docker.io/v2/": Forbidden Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the runtime sandbox reaches registries only through the in-fence pull-through mirror, so an image the mirror does not carry cannot be fetched — this is a limit of our sandbox, not of your stack; runtime evidence skipped.
C1 Data Protection — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These personal data controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks personal data controls.
C2 Access Controls — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These authorization controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks authorization controls.
C3 Audit Trail — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These audit controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks audit controls.
C4 Data Retention — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These retention controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks retention controls.
C5 Data-Subject Rights — not measured this run — Watchdog could not measure this here. That is a gap on our side — a collector, parser or image we have not built yet — and it is neither a defect in this repository nor evidence that the check would have passed. These data-subject rights controls are read from declarative annotations, request middleware, entity/column names and guard methods in a C# source model, and none was loaded on this run, so there was nothing to gather. That is a gap in this analyzer's language reach — not a finding that the repository lacks data-subject rights controls.
M4 Documentation accuracy — measured, with a gap in what it reached — Watchdog measured this, but not all of it. What it did not reach is a gap on our side — a collector, parser or image we have not built yet — so the numbers on that dimension cover less than the repository, and the part left out is not evidence that it would have passed. M4 checks only the claim kinds adjudicated at or above 95 % precision: links and versions (PREREGISTRATION version 9). Paths, command arguments, installs, environment variables, settings, projects, packages, routes, cd targets, infrastructure products and removed modules are read but not checked, and none of them is reported or counted.

Repo exclusion declarations: 10 pattern(s) declared (.gitattributes linguist-generated/vendored, .editorconfig generated_code) excluded 0 source file(s) from code-quality scoring. Declarations are the repo's own visible statement that a tree is machine-written or vendored — auditable in any diff, honored by GitHub the same way.

Limitations & what we did not check

Watchdog assesses the repository exactly as committed, and only the repository. By design it does not reach outside the source tree: the live cloud account, the running CI/CD pipeline, the host's branch-protection and approval rules, the production configuration, or a restore actually exercised against a backup are all out of scope. That boundary is a feature, not a gap — a repo-relative, deterministic scan re-runs identically on any commit and every finding opens at a real file and line, where a live audit can neither be reproduced nor traced. The visible consequence is that controls which leave no in-repo evidence are reported as "not evidenced" and excluded from the score rather than awarded a number a static scan cannot justify.

Per-dimension blind spots

For each dimension that was measured, what a static, repo-only scan structurally cannot see — the honest edge of the measurement, not a failure of it.

D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically — it cannot tell an essential decision tree from accidental tangle, nor see complexity that lives in data or configuration (large switch-case token tables, DSL lexers/parsers, data-as-code rule tables) rather than control flow: a tokenizer's many single-character cases read as high complexity though each branch is trivial.
D2 Cognitive Complexity: Cognitive-complexity heuristics approximate how hard code is to follow; genuine domain difficulty and well-named intent that eases reading are not captured.
D3 God Classes: "God class" is sized by members and responsibilities visible in the type — a deliberately broad facade over a coherent subsystem can read the same as an accidental grab-bag. For front-end JS the file-length check is cohesion-aware (a single-responsibility module — one class/IIFE — earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
D4 Code Duplication: Duplication is token-similarity — an in-process token-stream comparison over sliding windows, with type-aware normalization — so it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D7 Architectural Integrity: Layering is checked against detected/declared rules — an architecture whose boundaries live in convention or in code review, not in a rule a scanner can read, is not enforced here.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals — a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D13 REDACTED Scanning: REDACTED detection is signature- and entropy-based on the current tree — a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy — mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history — a freshly imported or squashed repository has no churn signal, and recent rewrites can mask a historically risky file.
D16 Bus Factor: Bus-factor is a time-decayed model of commit attribution (who has recently, repeatedly worked a file), not comprehension — pairing, review and reading-without-committing spread knowledge it can't see; bot commits and shared accounts still distort it.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
D19 Documentation Quality: Documentation quality publishes two things only: a runnable or packaged unit with no example, and a multi-project root README that maps none of its parts. It does not judge clarity, and its other checks (overview, licence, boilerplate, structure, empty sections, XML-doc coverage) are withheld after adjudication: their candidates are counted in the card's gaps, not shown as rows. A false statement in a document is M4's; units are .NET projects only.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
D26 Project Cohesion: Project focus is sized from members/namespaces per project — a project that is broad by deliberate design reads the same as one that has sprawled.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns — a secret that predates the available history, or never matched a signature, is not found (clean means "nothing matched in the history we can see").
D29 Static Analysis (SAST): SAST findings are pattern-based (semgrep) — it finds classes of bug it has rules for; logic flaws, auth/authorization gaps and issues needing runtime context are out of reach (and clean means "no rule matched").
D30 Dependency Vulnerabilities: CVE matching depends on accurate package/version metadata and on the advisory databases — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen. Coverage needs a RESOLVED graph: an unpinned REDACTED, or a pom without a resolved build, yields partial coverage rather than a clean verdict. An ecosystem the analyzer cannot scan is reported as unmeasured, never as clean.
D31 IaC & Container Security: IaC scanning checks Dockerfiles/Terraform/Kubernetes against best-practice rules — it cannot see the live cloud account, runtime configuration, or drift between the committed config and what is actually deployed.
D34 Knowledge Freshness: Freshness is decayed commit RECENCY, not comprehension — code read often but rarely committed reads as orphaned, and stable code that genuinely needs no changes is penalised the same as forgotten code; bot/squash commits distort it like the bus factor.
D35 Change Coupling: Change coupling is co-change in COMMITS — files split across separate commits, or coupled only through a shared config/build step, read as uncoupled, and a sweeping commit (rename/format) is excluded so it doesn't couple everything. It shows that files change together, not WHY: a high coupling can be a healthy cohesive pair as readily as a hidden leak.
D43 Malicious Dependencies: Only packages some vulnerability database has already NAMED as malicious are seen — a compromise published in the last hours, or never reported at all, is invisible here, and this dimension reading 10 is not evidence that a dependency is trustworthy. There is no typosquat or dependency-confusion analysis: a package nobody has reported is simply absent from the feeds. Coverage is the dependency scan's: an ecosystem that could not be scanned is disclosed as unmeasured, never as clean.
D44 Platform End-of-Life: The support table is FROZEN, so it goes out of date by losing RECALL: a release that ended support after the table was written is missed until the table is refreshed, and this dimension reading 10 is not evidence that a platform is current. Only platforms the repository DECLARES in a place this pass reads are seen — a runtime named only in a REDACTED (D31's subject), in a CI workflow (D29's), or in a file this pass does not parse (go.mod, a Gemfile ruby directive) is invisible here, which is why a repository declaring none of them abstains rather than scoring. Only frameworks with a PUBLISHED support policy are tracked: React, Flask and Express publish none, so their age cannot be judged and their absence from a report is not a statement that they are supported.
AX10 Code composition: Role is inferred from namespace/folder convention, not semantics — a domain concept living in a folder named "Services" reads as application, and the split is lines-of-code, not business value. The business-logic-share score is a SOFT, FLOORED signal: it contributes to the Architecture lens but is floored at the Critical gate, so an infrastructure-heavy design (a gateway, an ETL, a driver) is legitimately low without being nuked to zero.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present — it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
P4 Deployment & Rollback: Approval/branch-protection rules live in repository settings the scan cannot see — only their in-repo evidence (config files, workflows) is checked, so a control enforced purely in the host's settings reads as "not evidenced".
P5 DR & Backup: Backup/restore and disaster-recovery readiness is judged from in-repo evidence — a config that exists is not a tested restore, so the absence of positive evidence is reported as "not evidenced", never scored as present.
P6 Release Hygiene: Rollback/observability controls are inferred from repo artefacts (pipelines, dashboards-as-code) — controls configured in external tooling, with no in-repo trace, cannot be credited.

Dimensions

D1 · Cyclomatic Complexity5.9 / 10Adequate✓ Tool-verified

What it measures: How tangled the control flow is — methods with many branches are hard to test and change.

Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.

Maturity: Documented → Verified → Prevented · effective 5.9 / 10 · rule-coverage 100% · ceiling Prevented

84 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was DeltaAnalysis.apply at 115. A further 12 method(s) were over the threshold but excluded as flat dispatchers (a long switch/match over independent cases: many branches, almost no nesting), the largest being ExpressionVisitor.visitScalarExpression at 25 — they are counted neither in the figure above nor in this dimension's score. 8 files carry no cyclomatic complexity row at all for this reason — every one of their over-threshold methods was excluded, so the exclusion is disclosed nowhere in the file itself: kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/ExpressionVisitor.java (ExpressionVisitor.visitScalarExpression at 25), flink/src/main/java/io/delta/flink/sink/Conversions.java (FlinkToDelta.dataType at 22), spark/src/main/scala/org/apache/spark/sql/delta/DeltaParquetFileFormat.scala (DeltaParquetFileFormatBase.translateFilterForColumnMapping at 21), spark/src/main/scala/io/delta/sql/parser/DeltaSqlParser.scala (DeltaSqlAstBuilder.visitPrimitiveDataType at 19), spark/src/main/scala/org/apache/spark/sql/delta/actions/InMemoryLogReplay.scala (InMemoryLogReplay.append at 18), and 3 more not listed here. They are named here because the per-file figures other dimensions report are taken BEFORE this exclusion, so such a file can show a high maximum complexity elsewhere in this report and nothing here, with nothing to reconcile the two.

DeltaAnalysis.apply (cyclomatic 115)spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:90

ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67)spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:572

WriteIntoDelta.writeAndReturnCommitData (cyclomatic 61)spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala:136

IntervalParser.toMicroSeconds (cyclomatic 60)kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/IntervalParserUtils.java:110

VariantStatsData.forPrefixAndStatType (cyclomatic 52)spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:169

+ 79 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Bring the 3 bodies over 60 down to 60 or less in Cyclomatic Complexity — start with DeltaAnalysis.apply (cyclomatic 115), ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67), WriteIntoDelta.writeAndReturnCommitData (cyclomatic 61). — This score is capped by its worst body, so a finding fixed alone moves it by almost nothing — the next one down takes its place. Refactoring these 3 together lifts Cyclomatic Complexity from 5.9 to about 6.5/10, projected with the scoring formula itself and assuming each lands exactly at 60; a cleaner split scores higher.
Enforce Cyclomatic Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d1_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D2 · Cognitive Complexity5.4 / 10Adequate✓ Tool-verified

What it measures: How hard the code is for a person to follow, beyond raw branching.

Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.

Maturity: Documented → Verified → Prevented · effective 5.4 / 10 · rule-coverage 100% · ceiling Prevented

140 method(s) exceeded the cognitive complexity threshold of 15; the worst was VariantStatsData.forPrefixAndStatType at 173.

VariantStatsData.forPrefixAndStatType (cognitive 173)spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:169

DeltaAnalysis.apply (cognitive 152)spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:90

ExpressionUtils.dsv2PredicateToCatalystExpression (cognitive 107)spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:572

WriteIntoDelta.writeAndReturnCommitData (cognitive 96)spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala:136

IntervalParser.toMicroSeconds (cognitive 83)kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/IntervalParserUtils.java:110

+ 135 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Bring the 2 bodies over 120 down to 120 or less in Cognitive Complexity — start with VariantStatsData.forPrefixAndStatType (cognitive 173), DeltaAnalysis.apply (cognitive 152). — This score is capped by its worst body, so a finding fixed alone moves it by almost nothing — the next one down takes its place. Refactoring these 2 together lifts Cognitive Complexity from 5.4 to about 5.8/10, projected with the scoring formula itself and assuming each lands exactly at 120; a cleaner split scores higher.
Enforce Cognitive Complexity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.

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D3 · God Classes8.8 / 10Strong✓ Tool-verified

What it measures: Over-large classes that try to do too much ("god classes").

Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.

Maturity: Documented → Verified → Prevented · effective 8.8 / 10 · rule-coverage 100% · ceiling Prevented

103 god class(es) detected.

FileTooLong: sources/DeltaSQLConf.scala · ×42spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSQLConf.scala

TooManyMethods: DeltaErrorsBase · ×30REDACTED:186

ClassTooLong: TableMetadata · ×18icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:66

MethodTooLong: UCCommitCoordinatorClient.commitImpl · ×13storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:325

What to do

Resolve the 42 FileTooLong finding(s) in God Classes — start with actions.scala (2), tables.py (2), DeltaSQLConf.scala. — One of this dimension's main actionable groups (42 warning-level).
Resolve the 30 TooManyMethods finding(s) in God Classes — start with DeltaTable.scala (3), TableMetadata.java (2), DeltaLog.scala (2). — One of this dimension's main actionable groups (30 warning-level).
Resolve the 18 ClassTooLong finding(s) in God Classes — start with TableMetadata.java, DeltaV2MicroBatchStream.java, DeltaAnalysis.scala. — One of this dimension's main actionable groups (18 warning-level).
Enforce God Classes in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d3_recommendation.md · top locations in Appendix A, every location in findings.md.

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D4 · Code Duplication9.8 / 10Stronggated by 137 serious findings✓ Tool-verified

What it measures: Copy-pasted code that should be shared instead.

Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.

Maturity: Documented → Verified → Prevented · effective 9.8 / 10 · rule-coverage 100% · ceiling Verified

130 duplicated block group(s) detected. A further 7 rows report members as variants of one another; they aggregate block groups already counted above and are not themselves counted. 10 of the 137 are in trees this repository does not ship — vendored, example/demo, project-template, fixture and benchmark code — and are ranked below the shipped groups rather than excluded from them: the duplication there is real and is still counted in this dimension's score. The dimensions that publish a production-file census leave those trees out of theirs, so this count is deliberately drawn over the wider population.

Duplicated block (9 lines × 2) · ×13iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:219

Duplicated block (7 lines × 2) · ×11iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:188

Duplicated block (6 lines × 2) · ×9iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:181

Duplicated block (10 lines × 2) · ×8spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:90

Duplicated block (5 lines × 2) · ×7REDACTED:149

+ 55 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 13 Duplicated block (9 lines × 2) finding(s) in Code Duplication — start with BitPacking.java (3), DeltaToIcebergConvert.scala, DeltaOptimizeBuilder.scala. — One of this dimension's main actionable groups (13 warning-level).
Resolve the 11 Duplicated block (7 lines × 2) finding(s) in Code Duplication — start with CRCInfo.java (2), DeltaToIcebergConvert.scala, DeltaMergeBuilder.scala. — One of this dimension's main actionable groups (11 warning-level).
Resolve the 9 Duplicated block (6 lines × 2) finding(s) in Code Duplication — start with optimizablePartitionExpressions.scala (2), DeltaToIcebergConvert.scala, InterleaveBits.scala. — One of this dimension's main actionable groups (9 warning-level).
Enforce Code Duplication in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d4_recommendation.md · top locations in Appendix A, every location in findings.md.

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D5 · Coupling4.0 / 10Weak✓ Tool-verified

What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.

Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.

Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.

Maturity: Documented → Verified → Prevented · effective 4.0 / 10 · rule-coverage 100% · ceiling Prevented

10 production modules (npm+Python+sbt), 1 dependency cycle(s), 0 unstable depended-on module(s). Read from the build's own module declarations; a dependsOn spread (deps: _*) and a project whose directory a helper computes are not visible there; 1 module(s) off the main sequence, with abstractness counted on 9 of the 10 (the rest declare no modelled class or interface, export only macros, declare types in source no model reads, or have no source directory of their own).

Circular dependency

Off the main sequence: connectCommon

What to do

Resolve the 1 Circular dependency finding(s) in Coupling. — One of this dimension's main actionable groups (1 issue-level).
Enforce Coupling in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d5_recommendation.md · top locations in Appendix A, every location in findings.md.

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D6 · Cohesion (LCOM4)9.8 / 10Stronggated by 2 serious findings✓ Tool-verified

What it measures: Whether a class's methods are focused on a single responsibility.

Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.

Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.

Maturity: Documented → Verified → Prevented · effective 9.8 / 10 · rule-coverage 100% · ceiling Verified

2 of 103 classes have LCOM4 above 3.

Low cohesion: IcebergRESTCatalogPlanningClient (LCOM4 4) · ×2iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/IcebergRESTCatalogPlanningClient.scala:72

What to do

Resolve the 2 Low cohesion finding(s) in Cohesion (LCOM4) — start with IcebergRESTCatalogPlanningClient.scala, FileStatsHistogram.scala. — One of this dimension's main actionable groups (2 warning-level).
Enforce Cohesion (LCOM4) in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d6_recommendation.md · top locations in Appendix A, every location in findings.md.

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D7 · Architectural Integrity6.0 / 10Adequate✓ Tool-verified

What it measures: Whether the code respects its intended layering / architecture rules.

Method: Enforcement rung (Prevented/Verified/Documented) per checkable ADR via Roslyn, plus dependency cycles via the engine shared with D5/AX3. Deterministic, exact.

Maturity: Documented → Verified → Prevented · effective 6.0 / 10 · rule-coverage 100% · ceiling Prevented

No mechanizable ADR was identified, so enforcement is not measured. Dependency cycles not checked (no project-reference graph; where this repository's language has an import-cycle lens, cycles are reported there).

What to do

Enforce Architectural Integrity in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d7_recommendation.md.

Do you agree with this assessment?

D9 · Test Distribution9.8 / 10Exemplary✓ Tool-verified

What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.

Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.

Maturity: Documented → Verified → Prevented · effective 9.8 / 10 · rule-coverage 100% · ceiling Documented

6910 test methods: 6825 unit, 1 integration, 0 BDD, 84 e2e. The Python suite contributes 89 test function(s) across 11 file(s) declaring at least one — every `def test…` in a file pytest or unittest would collect, which is those frameworks' own definition of a case; a parametrize table counts once, so this is a floor. Its tier split is read from file names and paths only. The Scala suite contributes 6821 test case(s) across 545 file(s) in a test source set declaring at least one — every `test("…")`, `it("…")`, `property("…")` and `"…" in {…}` registration and every JUnit `@Test`, which is how munit, ScalaTest, utest, ZIO Test and specs2 declare a case; a case registered under a computed name is not counted, so this is a floor. Its tier split is INFERRED from paths and file names, except sbt's src/it source set, which the build declares.

✓ On the Gold path — maintain.

Detailed fixes: d9_recommendation.md.

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D13 · REDACTED Scanning10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.

Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Prevented

REDACTED scan ran and found no leaked secrets.

✓ On the Gold path — maintain.

Detailed fixes: d13_recommendation.md.

Do you agree with this assessment?

D14 · License Compliance10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether the licenses of third-party packages are compatible with your policy.

Method: Third-party package licenses resolved from declared package metadata and checked against the configured policy (allow/deny/copyleft). Deterministic; clean = no incompatible license found at metadata depth.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 of 4 declared JVM dependency artifact(s) use a banned license. Licences were resolved from the POMs Maven Central publishes, over the coordinates this repository's 1 Maven/Gradle manifest(s) declare with a version resolvable from the manifest itself — the same declaration-site closure this analysis reads for dependency currency. The JVM has no lockfile a checkout is guaranteed to carry, so this is deliberately NOT the transitive closure. A further 3 coordinate(s) are not published to Maven Central — another repository (Google's Maven hosts androidx), a SNAPSHOT, or a private artifact — so their licences are not readable from here and they are outside this verdict. ★ COVERAGE OF THIS VERDICT: it grades this repository's JVM dependencies and nothing else. The repository also declares an sbt build (REDACTED), a Python pyproject.toml/requirements.txt (pip/uv/Poetry) and package.json, and the licences of those dependency graphs were NOT read by this pass — a gap in this engine's coverage, not a statement about them. So this result says the graded closure carries no banned licence; it does NOT say this repository's licensing is clear.

✓ On the Gold path — maintain.

Detailed fixes: d14_recommendation.md.

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D15 · Churn × Complexity Hotspots9.8 / 10Stronggated by 10 serious findings✓ Tool-verified

What it measures: Files that change often and are also complex — the riskiest hotspots.

Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.

Maturity: Documented → Verified → Prevented · effective 9.8 / 10 · rule-coverage 100% · ceiling Documented

Top hotspots: spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala (36×21=756); spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala (3×115=345); spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala (10×22=220)

Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala · ×10spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2582

What to do

Resolve the 10 Hotspot finding(s) in Churn × Complexity Hotspots — start with OptimisticTransaction.scala, DeltaAnalysis.scala, ConflictChecker.scala. — One of this dimension's main actionable groups (10 warning-level).

Detailed fixes: d15_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D16 · Bus Factor9.1 / 10Exemplary✓ Tool-verified

What it measures: Whether knowledge is concentrated in too few people (the "bus factor").

Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.

Maturity: Documented → Verified → Prevented · effective 9.1 / 10 · rule-coverage 100% · ceiling Documented

68 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java. Counted over 792 of the 1126 production source files in this repository: 331 are under the ~2,400-byte size floor this dimension measures over, and the remaining 3 have no attributable history left to measure.

Off-boarding risk: anonymized user #1 · ×7

Further sole-owners (lower concentration)

✓ On the Gold path — maintain.

Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.

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D17 · Explicit Debt9.7 / 10Stronggated by 378 serious findings✓ Tool-verified

What it measures: Acknowledged debt left in the code — TODOs, dead code, suppressed warnings.

Method: Roslyn syntactic debt markers (suppressions/TODO/FIXME/HACK/empty-catch/commented-code/Obsolete) plus SymbolFinder dead-code analysis; weighted-debt-per-KLoC density deducted 2.0x per unit. Deterministic, exhaustive.

Maturity: Documented → Verified → Prevented · effective 9.7 / 10 · rule-coverage 100% · ceiling Prevented

378 deducted task-comment markers across 277583 LoC (0.1/KLoC) → score 9.7. Task comments only: this repository's language is read without a compiler, so D17's suppression, dead-code and commented-out-code arms did not run and this score counts fewer marker kinds than a .NET repository's would.

TodoComment · ×354storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:317

HackComment · ×22spark/src/test/scala/org/apache/spark/sql/delta/test/CustomCatalogs.scala:93

FixmeComment · ×2spark/src/test/scala/org/apache/spark/sql/delta/DeltaInsertIntoTableSuite.scala:1572

What to do

Resolve the 354 TodoComment finding(s) in Explicit Debt — start with DeltaV2MicroBatchStream.java (8), SnapshotImpl.java (7), DeltaTempViewStoredPlanRefreshTests.scala (5). — One of this dimension's main actionable groups (354 warning-level).
Resolve the 22 HackComment finding(s) in Explicit Debt — start with HiveTableOperations.java (8), HiveCatalog.java (5), CustomCatalogs.scala (2). — One of this dimension's main actionable groups (22 warning-level).
Resolve the 2 FixmeComment finding(s) in Explicit Debt — start with DeltaInsertIntoTableSuite.scala, DeltaCommandInvariants.scala. — One of this dimension's main actionable groups (2 warning-level).
Enforce Explicit Debt in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.

Detailed fixes: d17_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D19 · Documentation Quality10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether the project's documentation is clear, complete, and useful.

Method: Every README, docs/ document and root guide parsed by its markup and measured in Unicode letters. Published: a runnable or packaged .NET project whose README (or a document it links, or a root guide) shows no example, and a root README naming none of three or more projects. Overview, licence, boilerplate, wall-of-text, empty-section and XML-doc rows are measured and withheld (counted in gaps) after adjudication. Deterministic, exhaustive, advisory.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

1 of 1 documentation facets pass in full. 63 document(s) read across 1 unit(s).

✓ On the Gold path — maintain.

Detailed fixes: d19_recommendation.md.

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D20 · ADR Quality10.0 / 10Exemplary○ Nothing flagged

What it measures: Whether architecture decisions are recorded well (context, decision, consequences).

Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

0 of 3 evaluated ADRs have a defect readable from the log itself (a missing or empty section, no title, a single option, consequences with no cost, no status, a missing enforcement field, a status the log contradicts, a dangling link, an unlinked second decision on one question). How well each record argues its case is not measured.

✓ On the Gold path — maintain.

Detailed fixes: d20_recommendation.md.

Do you agree with this assessment?

D26 · Project Cohesion3.3 / 10Weak✓ Tool-verified

What it measures: Whether each project is a focused, coherent unit rather than an oversized grab-bag.

Method: Project size overshoot penalties (LoC / public-type count / namespace count, 2-of-3 flag) weighted by log magnitude. Exhaustive across projects, deterministic, LLM-independent.

Maturity: Documented → Verified → Prevented · effective 3.3 / 10 · rule-coverage 100% · ceiling Documented

1 of 3 build units (Python, npm) flagged as possibly oversized/incoherent.

Projects may be oversized for their cohesion

What to do

Resolve the 1 Projects may be oversized for their cohesion finding(s) in Project Cohesion. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d26_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D28 · Secrets (history)9.0 / 10Adequategated by 1 critical finding✓ Tool-verified

What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.

Method: REDACTED scan via TWO gitleaks detect passes in an isolated checkout — the full git history, then a second --no-git pass over the working tree as it stands — merged and de-duplicated by (rule, file, line); each match flagged High. Both invocations are recorded in the audit trail. Exhaustive; when the tool is absent, or when its output cannot be parsed into the expected shape, the dimension is WITHHELD as an explicit measurement gap on our side — unscored and excluded from the lens, never a hedged middling score.

Maturity: Documented → Verified → Prevented · effective 9.0 / 10 · rule-coverage 100% · ceiling Documented

1 finding(s): 0 critical, 1 high, 0 medium, 0 low. Remediation for historically-committed secrets is credential rotation — they remain in history regardless of later deletion.

REDACTED

What to do

Resolve the 1 REDACTED finding(s) in Secrets (history) — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
Resolve the 1 Rotate the exposed credentials finding(s) in Secrets (history). — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d28_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D29 · Static Analysis (SAST)1.7 / 10Critical✓ Tool-verified

What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.

Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.

Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).

Maturity: Documented → Verified → Prevented · effective 1.7 / 10 · rule-coverage 100% · ceiling Documented

11 finding(s): 0 critical, 10 high, 1 medium, 0 low. semgrep hit a parse error in 294 file(s) — `connectors/golden-tables/src/main/resources/golden/124-decimal-decode-bug/_delta_log/00000000000000000000.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000000.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000001.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000002.json`, `connectors/golden-tables/src/main/resources/golden/125-iterator-bug/_delta_log/00000000000000000003.json`, … (+289 more) — so no absence of findings in them is evidence of anything, and nothing in them was analysed. Fix the syntax error (or exclude the file deliberately) and re-scan to cover them. Separately, one or more rules could not re-parse an embedded snippet in 11 file(s) (e.g. a workflow `run:` block read as shell). Those files WERE scanned and their other rows are unaffected; only those rules' view of those snippets is missing.

REDACTED

What to do

Resolve the 4 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (2), REDACTED, REDACTED. — One of this dimension's main actionable groups (4 issue-level).
Resolve the 3 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (3). — One of this dimension's main actionable groups (3 issue-level).
Resolve the 2 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED, REDACTED. — One of this dimension's main actionable groups (2 issue-level).

Detailed fixes: d29_recommendation.md · top locations in Appendix A, every location in findings.md.

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D30 · Dependency Vulnerabilities7.5 / 10Adequategated by 4 critical findings✓ Tool-verified

What it measures: Whether any dependency has a known published vulnerability (CVE), direct or transitive, in ANY ecosystem the repository declares — Dart pub, Elixir and Erlang via Hex, Go modules, Java and Kotlin via Maven/Gradle, JavaScript/npm, .NET/NuGet, PHP/Composer, Python/PyPI, RubyGems, Rust/Cargo and Swift.

Method: Dependency-CVE scan across every ecosystem the repository declares, scored ONCE. Three sources are unioned and deduplicated by advisory identity (rule id + alias closure, CVE<->GHSA) scoped to package+version, keeping the worst severity: `osv-scanner --recursive` over osv.dev for Dart pub, Elixir/Hex (and Erlang, whose `rebar.lock` syft first converts to a CycloneDX SBOM the scanner reads, with rows attributed back to the lock), Go, Java and Kotlin via Maven/Gradle (and Scala, whose sbt build's pinned direct declarations are written into a CycloneDX SBOM the scanner reads, with rows attributed back to the build file), npm, PHP/Composer, Python/PyPI, RubyGems, Rust/Cargo and Swift; `trivy fs --scanners vuln` for npm lockfiles; and `dotnet list package --vulnerable --include-transitive` for NuGet (with per-advisory collapse of the project x target-framework fan-out), plus a DECLARED-dependency arm that resolves a published gem's gemspec against rubygems.org where no Gemfile.lock is committed. `SeverityScore(c,h,m,l, normalizer 8.0)`. NotApplicable only when NO ecosystem is readable; if any applicable ecosystem could not be scanned the findings are REPORTED and the score is withheld. Supersedes the npm and OSV arms, retired 2026-09-05.

Maturity: Documented → Verified → Prevented · effective 7.5 / 10 · rule-coverage 100% · ceiling Documented

4 finding(s): 0 critical, 4 high, 0 medium, 0 low.

REDACTED

What to do

Resolve the 4 High CVE finding(s) in Dependency Vulnerabilities — start with REDACTED (3), REDACTED. — One of this dimension's main actionable groups (4 issue-level).

Detailed fixes: d30_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D31 · IaC & Container Security9.4 / 10Adequategated by 1 critical finding✓ Tool-verified

What it measures: Whether Dockerfiles / Terraform / Kubernetes config follow security best practices.

Method: IaC/container misconfiguration scan via trivy config (REDACTED/Terraform/K8s/Helm/CloudFormation); severity rules to 0-10 moderate normalizer. NotApplicable without manifests. Exhaustive, deterministic.

Maturity: Documented → Verified → Prevented · effective 9.4 / 10 · rule-coverage 100% · ceiling Documented

4 finding(s): 0 critical, 1 high, 3 medium, 0 low.

REDACTED

What to do

Resolve the 1 High IaC finding(s) in IaC & Container Security — start with REDACTED. — One of this dimension's main actionable groups (1 issue-level).
Resolve the 3 Medium IaC finding(s) in IaC & Container Security — start with REDACTED (3). — One of this dimension's main actionable groups (3 warning-level).

Detailed fixes: d31_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D34 · Knowledge Freshness7.6 / 10Adequategated by 8 critical findings✓ Tool-verified

What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned — last understood long ago by someone now gone quiet. The sibling of the bus factor: D16 asks who owns it, D34 asks whether anyone still knows it.

Method: File orphaning as total living-knowledge decay below one focused-commit's worth within a year, computed per-file from the D16 decay model. Exhaustive, deterministic over fixed history.

Maturity: Documented → Verified → Prevented · effective 7.6 / 10 · rule-coverage 100% · ceiling Documented

188 of 795 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/LogSegment.java. Counted over 795 of the 1126 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

Orphaned knowledge · ×8kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/LogSegment.java:1

Orphaned file · ×180spark/src/main/scala/org/apache/spark/sql/delta/skipping/clustering/ClusteredTableUtils.scala:1

Further orphaned files (smaller)

What to do

Resolve the 180 Orphaned file finding(s) in Knowledge Freshness — start with RelocatedStreamingClassesShims.scala (3), DeltaTableBuilder.scala (2), DeltaOptimizeBuilder.scala (2). — One of this dimension's main actionable groups (180 recommendation-level).
Resolve the 8 Orphaned knowledge finding(s) in Knowledge Freshness — start with LogSegment.java, DeltaMergeBuilder.scala, Protocol.java. — One of this dimension's main actionable groups (8 issue-level).
Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d34_recommendation.md · top locations in Appendix A, every location in findings.md.

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D35 · Change Coupling9.9 / 10Stronggated by 6 serious findings✓ Tool-verified

What it measures: Whether files that change together actually belong together — pairs that repeatedly co-change in git history despite having no explicit code dependency, surfacing the hidden/logical coupling (and boundaries in the wrong place) a static scan can't see.

Method: Pairwise co-occurrence over the per-commit file sets in git history (production source only — tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file ≥10 revisions, ≥5 shared commits, ≥50% strength); sweeping commits excluded. Deterministic over fixed history.

Coverage: Population: PRODUCTION source files only — test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real production↔production coupling. Pairs ranked by Degree-of-Coupling. A non-source file is never a coupling PARTICIPANT either: documentation, schemas, config and data files are dropped with the rest, so a code↔docs pair — a command and the reference page that restates it — is not reported however strongly the two co-change; nor is coupling that runs THROUGH a build step or config file.

Maturity: Documented → Verified → Prevented · effective 9.9 / 10 · rule-coverage 100% · ceiling Documented

Strongest change-coupling: TransactionBuilder.java↔TransactionImpl.java 70%; DefaultExpressionUtils.java↔ExpressionVisitor.java 69%; ClassicMergeExecutor.scala↔InsertOnlyMergeExecutor.scala 67%

Change coupling: TransactionBuilder.java ↔ TransactionImpl.java · ×6kernel/kernel-api/src/main/java/io/delta/kernel/TransactionBuilder.java:1

What to do

Resolve the 6 Change coupling finding(s) in Change Coupling — start with TransactionBuilder.java, DefaultExpressionUtils.java, ClassicMergeExecutor.scala. — One of this dimension's main actionable groups (6 warning-level).

Detailed fixes: d35_recommendation.md · top locations in Appendix A, every location in findings.md.

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D36 · Supply-chain Provenance & Signing5.0 / 10Adequate✓ Tool-verified

What it measures: Whether the build pipeline provides supply-chain integrity — generated provenance/attestation, signed artifacts (cosign/sigstore), an SBOM, and pinned build actions. Presence of the configuration, not a runtime guarantee.

Method: Supply-chain provenance/signing read deterministically from CI/build config (.github/workflows, .gitlab-ci.yml, azure-pipelines, Jenkinsfile, .circleci) + the release surface: four signals — generated provenance/attestation (SLSA/in-toto/actions-attest), artifact signing (cosign/sigstore/gitsign), an SBOM (syft/sbom-action/*.spdx.json/*.cdx.json), and SHA-pinned build actions — scored 10·present/denom. NotApplicable without a build pipeline. Detects configuration presence, not runtime enforcement.

Maturity: Documented → Verified → Prevented · effective 5.0 / 10 · rule-coverage 100% · ceiling Documented

2/4 supply-chain integrity signals present (provenance, signing, SBOM, pinned actions).

REDACTED

+ 1 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 10 REDACTED finding(s) in Supply-chain Provenance & Signing — start with REDACTED, REDACTED, REDACTED. — One of this dimension's main actionable groups (10 warning-level).
Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing — start with REDACTED. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d36_recommendation.md · top locations in Appendix A, every location in findings.md.

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D43 · Malicious Dependencies10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether any dependency the repository declares is published as MALICIOUS rather than merely vulnerable — a package that is an attacker's work, in any ecosystem osv-scanner reads. Scored apart from D30 because the answer is binary: there is no safe version to upgrade to, and the fix is to remove the package and rotate every credential it could have read.

Method: The same dependency scan D30 reads, partitioned on the scanner's own classification rather than rescanned: a row is MALICIOUS when its id is in the `MAL-` space (the ossf/malicious-packages feed) OR its `database_specific.cwe_ids` carries `CWE-506` ("Embedded Malicious Code"). Both channels are structural; the summary text is deliberately NOT read, because a malicious-package record whose summary says only "Critical severity vulnerability" is a real shape ([GHSA redacted]) and a text matcher misses it. Scored BINARY: any surviving row is 0, whatever its severity and however many CVEs sit beside it — a hostile dependency is not a quantity. Applicability and degradation are D30's: NotApplicable only when no ecosystem is readable, and an unscannable ecosystem degrades rather than reading clean. SCORED, not informational.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

No dependency in any ecosystem this repository declares is published as malicious.

✓ On the Gold path — maintain.

Detailed fixes: d43_recommendation.md.

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D44 · Platform End-of-Life10.0 / 10Exemplary✓ Tool-verified

What it measures: Whether anyone still ships security patches for the platform this repository RUNS ON — the runtime it pins and the framework majors its own constraints hold it to. Separate from D12 because the question differs: a current Django on an end-of-life Python is perfectly up to date and completely unsupported, and the fix is a migration rather than a version bump. What the repository says it merely SUPPORTS is never charged.

Method: End-of-life PLATFORM read from the repository's own declarations and graded against a FROZEN, dated table of vendor support dates — no network, no feed, no API, so this dimension answers identically inside a closed scan fence. Two subjects: a RUNTIME the project pins (a single or all-end-of-life TargetFramework, a .nvmrc or .python-version, a requires-python CAP) and a FRAMEWORK major a dependency constraint cannot move off (a caret, tilde or exact version; `vue@^2.7.16` pins Vue 2). A FLOOR is deliberately never charged — `requires-python = ">=3.8"` states what a package SUPPORTS, not what it runs on — and a multi-target project is charged only when EVERY target is out of support. Runtime 4.0/product capped 8.0, framework 1.5 capped 4.5. The table is safe to freeze because a statement about support that ended in the past cannot become false: it loses recall as it ages, never precision, and a test asserts every entry predates the freeze date. Disjoint from D31 (a container image's OS layer) and D29 (the toolchain a CI workflow installs). Abstains when the repository declares no platform this pass reads — never scores it clean.

Maturity: Documented → Verified → Prevented · effective 10.0 / 10 · rule-coverage 100% · ceiling Documented

0 end-of-life runtime(s) and 0 end-of-life framework(s), read from 2 platform declaration(s) and 9 dependency declaration(s). This dimension reads what the repository says about ITSELF — a pinned target framework, a version file, a capped requires-python, a Rust toolchain pin, a framework major a constraint cannot move off. A FLOOR is deliberately never charged: `requires-python = ">=3.8"` states what the package SUPPORTS, not what it runs on, and a well-maintained library declares exactly that while running its own CI on a current release. The end-of-life facts are FROZEN and dated, so this dimension needs no network and answers identically inside a closed scan fence; as the table ages it loses recall and never precision, because a statement about support that ended in the past cannot become false. The OS layer of a container image is D31's question and the toolchain a CI workflow installs is D29's; this row is neither.

✓ On the Gold path — maintain.

Detailed fixes: d44_recommendation.md.

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Frontend & cross-cutting dimensions

R = React/JS · M = Maturity · P = Readiness.

AX10 · Code composition9.9 / 10Exemplary✓ Tool-verified

Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified. How each file's role is decided, because the split is only as good as that: a generated name or a build-output tree makes it Generated, a test project makes it Test, and otherwise the file's NAMESPACE and PATH words are matched against fixed vocabularies in a fixed ORDER — domain, then infrastructure, then application — so a file whose words hit two layers is counted under the earlier one. A production file matching none of them counts as application, so that share reads 'application or unclassified' rather than a measured application layer. Roles come from naming convention, never from what the code does. On this repository the split was taken from the source tree on disk rather than from a loaded .NET workspace, so a file's role is decided by its PATH segments alone — no declared namespace was available to add to the evidence — and generated output is excluded from the census entirely rather than counted as a generated share.

Method: Roslyn line-count by code ROLE: every source file classified Domain/Application/Infrastructure/Test/Generated by namespace + path convention (the shared CodeRoleClassifier), then significant lines summed per role. Deterministic; the advisory score is the business-logic (domain+application) share of production code.

Coverage: Population: ALL source files, each bucketed into ONE of five roles (Domain/Application/Infrastructure/Test/Generated) by namespace + path convention — a file whose layer isn't named in the convention falls to Application (the neutral default), and the split is line-count, not semantic depth or business value.

What to do

The domain core is a small share of production code, but most of the rest matched no layer vocabulary at all — so this is not yet an anemic-domain finding. The namespace/path convention could not place that code, which makes the composition above a statement about the naming, not about the design. Name the layers (or check that the repository's conventions differ from the ones this check knows) before reading a thin domain into it.

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AX3 · Project dependency cycles5.8 / 10Adequate✓ Tool-verified

Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).

Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.

The projects spark → sparkV1 → spark (one cycle inside a mutually-dependent group of 3 projects) form a reference cycle. Cyclic dependencies prevent independent build/test/deploy, blur ownership, and tend to grow into a big ball of mud. Break the cycle by extracting the shared types into a separate project both can reference.

What to do

Break project reference cycles by extracting shared abstractions into a separate project; keep the graph a DAG.

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AX4 · Dependency direction10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.

Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.

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AX6 · Interface segregation10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether interfaces stay focused rather than fat — the Interface-Segregation principle (SOLID 'I').

Method: Roslyn scan: public interface declared-member counts (accessors fold into their property/event); fat-interface threshold (over 15 declared members) flagged per type. Each finding also reports the distinct-OPERATION count — members counted by name, so an overload group counts once — which decides whether it states the caller-side ISP harm or the implementer-side burden of an overload set. TypeScript: exported interfaces that declare behaviour, counted over their REQUIRED operations (method signatures and function-typed properties with no `?`, once per signature) — data-shape interfaces and ambient .d.ts declarations are outside the population; JavaScript declares no interfaces and is not applicable. Deterministic, type-level.

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GD1 · Unfinished & placeholder code10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Unreviewed-generation residue in this repository's Scala: methods whose whole body is still `???` or a "not implemented" throw where nothing overrides them, and placeholder text (lorem ipsum, changeme/replace_me…) left in strings of non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.

Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.

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IC1 · Incompleteness & stubs8.5 / 10Strong✓ Tool-verified

Other · Code Health — Unfinished work detected by code SHAPE, not keywords, in this repository's Scala: methods whose body is `???` or only throws a "not implemented" error, methods that take inputs and return a constant or do nothing, dead `if (false)` branches, and skeleton classes most of whose methods are holes.

Method: Roslyn syntax scan: incompleteness by code shape (constant-returning methods, async-never-await, #if false branches, guards that return what the code already falls through to, tests an earlier guard already decided, comparisons against NaN, skeleton types), not keyword-gated. Deterministic, code-shape heuristic.

`mergeWriteOptionsIntoHadoopConf` takes parameters but its body is empty — it accepts inputs and does nothing. Either implement it or remove it. — spark/src/main/scala-shims/spark-4.0-4.1/DataSourceUtilsShims.scala:22
`extractAndInjectVariantStats` takes parameters but its body is empty — it accepts inputs and does nothing. Either implement it or remove it. — spark/src/main/scala-shims/spark-4.0/VariantShreddingShims.scala:34
A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead. (×8) — iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergFileManifest.scala:200, iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergSchemaUtils.scala:47, spark/src/main/scala/org/apache/spark/sql/delta/AllowedUserProvidedExpressions.scala:41, …
A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something. (×7) — kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/DeltaIcebergCompatV2Suite.scala:52, kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/DeltaIcebergCompatV2Suite.scala:58, kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/IcebergWriterCompatV1Suite.scala:765, …

What to do

Finish or delete the unfinished stubs (functions that throw "not implemented", or whose body is empty or a bare constant) — they are dead surface that looks live.
Clear the softer debt: re-enable or delete `ignore`d and `pending` tests, decide whether each empty method or UnsupportedOperationException is deliberate (and say so in a comment), and replace a bare `// scalastyle:off` or `@nowarn` with targeted, justified suppressions.

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M1 · Documentation (README)7.0 / 10Strong✓ Tool-verified

Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.

Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.

538 code files changed in the last 6 months but the README was not touched — it may no longer reflect the system.

What to do

Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 2 of 5 project(s) that lack one — worth up to 0.8 pts.
Review the README against recent changes; refresh the parts that drifted.

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M2 · Architecture documentation4.0 / 10Weak✓ Tool-verified

Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.

Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.

4 ADR-shaped document(s) detected by content — `protocol_rfcs/concurrent-identity-columns.md`, `protocol_rfcs/file-type.md`, `protocol_rfcs/iceberg-v4-metadata.md`, `protocol_rfcs/template.md`. They are not under a conventional ADR folder (docs/adr/) and are not named NNNN-title.md, and this check found them by their decision signature rather than by where they live — so a reader who does not already know these paths has no route to them. Detected by content signature only: records kept outside the repository, or written without a Status/Decision/Consequences shape, are not visible to this check and are not counted here.

What to do

Move ADRs under docs/adr/ (or docs/adrs/) and name them NNNN-title.md so they're easy to find.

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M3 · Folder & project structure10.0 / 10Exemplary✓ Tool-verified

Maturity · Maturity — Whether the repo is organised deliberately — src/test separation and consistent project naming.

Method: Filesystem scan: src/test folder separation and namespace-prefix consistency (majority RootNamespace agreement). Exhaustive across projects, deterministic.

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M4 · Documentation accuracy10.0 / 10Exemplary○ Nothing flagged

Maturity · Maturity — Whether the README actually describes the code that exists (LLM-judged, advisory).

Method: Judged by language model at low temperature: README accuracy versus actual projects, within a disclosed tolerance. Advisory, not a measured number.

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P1 · CI/CD gates10.0 / 10Exemplary○ Nothing flagged

Readiness · Readiness — Whether an automated pipeline builds and tests every change.

Method: Filesystem scan: CI workflow files (.github/workflows, .gitlab-ci.yml, etc.) for build and test stages. Exhaustive, deterministic.

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P10 · Library API & versioning10.0 / 10Exemplary○ Nothing flagged

Readiness · Readiness — For a library: a deliberate (small) public API surface and explicit semantic versioning so consumers can depend on it safely.

Method: Roslyn scan: public API surface area and semantic-versioning markers (SemVer attributes, changelog entries) for libraries; off .NET, a library is the ecosystem's publication act (an npm package that is not private and names an entry point, a PyPI distribution with a build system, a Rust library crate, a Maven/Gradle module that publishes, a Go module with no package main, a gemspec, a Composer library, a SwiftPM library product, a pub.dev or Hex package), its surface is the share of types the language model records as public (Rust, Swift, Java, Kotlin, Go, Dart; not measured where the model records no type visibility or, as in TypeScript, only module-level export), and its version is read from the manifest, a semver CHANGELOG, release tooling or semver git tags. Exhaustive, deterministic.

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P2 · Observability5.0 / 10Adequate✓ Tool-verified

Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.

Method: Filesystem/Roslyn scan: structured-logging frameworks (Serilog, NLog), OpenTelemetry, and health-check endpoint patterns. Exhaustive, deterministic.

Only 1/3 runnable modules use logging (modules with no entry point or server are excluded — they are libraries a runnable module hosts). Silent: `.`, `dev`.

What to do

Extend structured logging to the remaining runnable modules so everything you run is diagnosable in production.
Consider OpenTelemetry tracing/metrics (opentelemetry-java or Micrometer) and a health-check endpoint (Spring Boot Actuator's /actuator/health, or a /health route) for operability.

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P3 · Security & performance tooling5.0 / 10Adequate✓ Tool-verified

Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).

Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.

What to do

Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.

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P4 · Deployment & Rollback7.0 / 10Strong✓ Tool-verified

Readiness · Readiness — Whether releases are automated and safely reversible (probes, rolling updates, approval gates) — from manifests/pipeline files, not the live environment.

Method: Filesystem scan: deployment manifests/IaC (K8s YAML, Helm, Terraform) for rolling updates, probes, approval gates, migration hooks. Exhaustive, deterministic.

Deployment is orchestrated by compose, but no service declares a `healthcheck:` and nothing pins a previous image to fall back to — the runtime can tell that the container is up, not that it is serving, so a bad release is harder to detect and reverse.

What to do

Add a `healthcheck:` to the served compose service — probing the endpoint it already answers on where it has one — with `depends_on: condition: service_healthy` on whatever waits for it, and keep the deployed image tag immutable and recorded so rolling back is re-pointing at the previous tag rather than rebuilding.

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P5 · DR & Backup4.0 / 10Weak✓ Tool-verified

Readiness · Readiness — Whether disaster recovery is planned and codified — backups, geo-recovery, RTO/RPO, persistence guarantees — from IaC + container manifests + docs, never the live cloud.

Method: Filesystem scan: disaster recovery, backup, geo-recovery, RTO/RPO, persistence guarantees from IaC, manifests, and docs. Exhaustive, deterministic, never a live environment.

What to do

Document RTO/RPO and a tested restore procedure (a backup config alone isn't disaster recovery).
No persistence guard on critical data stores — use Docker named volumes (or your orchestrator's persistent-volume equivalent) so the data store can't be wiped by a container recreate (or, in cloud, set purge-protection / soft-delete / prevent_destroy).

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P6 · Release Hygiene10.0 / 10Exemplary✓ Tool-verified

Readiness · Readiness — Whether releases are traceable — a maintained changelog and explicit version stamping.

Method: Filesystem scan: changelog file presence and version tags in csproj or git tags. Exhaustive, deterministic.

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PF1 · Benchmark discipline8.0 / 10Strong✓ Tool-verified

Readiness · Performance — Whether the code protects its performance with benchmarks — a benchmark suite, allocation/memory measurement, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.

Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI; off .NET, the same ladder over Go testing.B, Rust criterion/#[bench]/divan, JMH/kotlinx-benchmark, pytest-benchmark/asv/pyperf, tinybench/mitata/vitest bench/benchmark.js and Swift package-benchmark — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.

A JMH/Jetpack Benchmark suite exists but nothing turns on its allocation measurement — allocations (the main way hot code pressures a garbage collector or allocator) aren't being measured. — kernel/kernel-benchmarks/src/test/java/io/delta/kernel/benchmarks/BenchmarkParallelCheckpointReading.java

What to do

Run JMH with the GC profiler (`-prof gc`, or addProfiler(GCProfiler.class)) so allocation rate regressions are visible, not just time.

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PF2 · Allocation hygiene6.3 / 10Adequate✓ Tool-verified

Readiness · Performance — Whether the code is written to minimise allocations so it doesn't pressure its host's memory manager — buffer/slice views over copies, object pooling, stack or value-type allocation, and buffer writers. Reward-only: credited where present, never penalised where a simpler style is fine.

Method: Production-source scan: density (per 1k LoC) of allocation-aware APIs — in .NET Span/Memory, ArrayPool/ObjectPool, stackalloc, ValueTask, value-type structs, IBufferWriter, string.Create, SkipLocalsInit; off .NET, with comments and strings blanked, Go's sync.Pool, preallocated slices/maps, Grow, strconv.Append* and buf[:0] reuse; the JVM's NIO buffer views, MemorySegment, primitive collections, pools and literal presizes (plus Kotlin primitive arrays and value classes, Scala AnyVal and @specialized); Swift's reserveCapacity, ContiguousArray, withUnsafe* access and ~Copyable. Activated off .NET on the same floor (400 lines, and benchmarks or 8 uses); Rust and garbage-collected scripting languages are not applicable. Reward-only. Deterministic, syntax/text detection.

What to do

Raise allocation-aware density on the hot paths — currently 155 use(s) across 253,481 production line(s) (~0.6/1k). More of the idioms below on the allocation-heavy paths climbs this toward 10.
Java: on hot paths, work through buffer views (ByteBuffer/LongBuffer slices, MemorySegment) instead of copies, avoid boxing with primitive collections (fastutil, Eclipse Collections, HPPC, Trove), presize collections and StringBuilders, and pool expensive buffers (Netty's pooled allocator, commons-pool).
Scala: on hot paths, make small wrappers value classes (extends AnyVal), @specialized generic code over primitives, use primitive collections, and presize builders.

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PF3 · Async & latency hygiene10.0 / 10Exemplary✓ Tool-verified

Readiness · Performance — Whether asynchronous code stays responsive — it avoids sync-over-async blocking (a .NET .Wait()/.GetAwaiter().GetResult(), a time.sleep or blocking HTTP call inside a Python coroutine, a *Sync call inside an async JavaScript function, block_on inside a Rust async fn, runBlocking inside a Kotlin suspend function, block() inside a Reactor publisher) that stalls a thread or event loop and risks deadlock, and, where the code is a reusable library on .NET, awaits with ConfigureAwait(false) so it never captures and stalls its caller's context.

Method: Production-source scan: sync-over-async blocking counted everywhere — .Wait()/.GetAwaiter().GetResult() in .NET; off .NET, read from the language model, a blocking call inside an async function (Python, TS/JS, Rust, Kotlin, Swift, Dart) or inside a Java method returning a Reactor Mono/Flux or a Scala method returning a Future or effect — and, for a .NET library with ≥5 awaits, the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.

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S1 · Web-Security Posture8.0 / 10Strong✓ Tool-verified

Other · Security — Read from this repository's Scala source and the Java beside it: cryptographic hygiene (weak hash or cipher, key material fixed in the source) and outbound TLS (certificate validation, protocol version) — facts about code that hold whether or not it serves anything itself. This repository builds on an HTTP-server library (REDACTED:1397 — depends on `jetty-server`) but serves no HTTP of its own: its production source starts no server (no `newServerAt`/`bindAndHandle`, server builder, `Server.serve`, `Http.serve`, tapir server interpreter or Netty HTTP pipeline), declares no application one runs (no Play application, servlet, cask `MainRoutes`, `HttpApp` or twitter-server), so it is a library whose server controls belong to the application that serves it — HTTPS enforcement, HSTS, cookie flags and input validation are N/A here, as they are for a C# library.

Method: Roslyn plus filesystem scan: HSTS/security headers, secure cookies, input validation, middleware order, weak crypto (MD5/SHA1/DES); HTTPS-metadata context-aware. On a repository with no .NET source it reads JavaScript/TypeScript, Dart, Ruby, Scala, Rust or Elixir source itself (test, vendored, generated and minified paths not) for the arms that hold whether or not the code serves HTTP: a weak hash or cipher, key material fixed in the source, a TLS client that accepts any certificate, and (JavaScript/TypeScript, Ruby, Scala, Rust and Elixir) an obsolete TLS version; the server controls are not assessed there, and a Dart, Ruby, Scala, Rust or Elixir repository that serves no HTTP of its own is N/A on them. Deterministic.

MD5/SHA1 is computed here, and both are collision-broken. If this digest protects anything — a signature, an integrity or tamper check, a credential, or any value an attacker can influence — that is a real weakness: use SHA-256+ (`MessageDigest.getInstance("SHA-256")`) for content integrity, or a KDF (bcrypt/Argon2/scrypt) for password storage. If it only derives a non-security identifier (a cache key, an avatar URL, an ETag), collision resistance carries no security consequence here; make that intent explicit instead — a non-cryptographic hash such as xxhash or murmurhash says it in code — since the algorithm alone cannot distinguish the two uses. Where a protocol this code does not own fixes the digest (a k-anonymity range query, a legacy signature format), the protocol decides; say so beside the call. — spark/src/main/scala/org/apache/spark/sql/delta/LastCheckpointInfo.scala:286

What to do

Review each MD5/SHA1 use by what it protects: replace it with SHA-256+ (or a KDF for passwords) where the digest is security-relevant, and switch it to a non-cryptographic hash (xxhash, murmurhash) where it only derives an identifier such as a cache key.

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X1 · Async correctness10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.

Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.

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X12 · Unreachable branch10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether any branch is dead by construction — a switch arm whose label can never equal a case-normalised subject, or an `else if` whose predicate the arm above has already swallowed.

Method: Roslyn syntax + semantics: switch labels compared against the subject's own case normaliser, and if/else-if chains checked for a literal an earlier arm's containment test already swallows. Deterministic, provable per finding. Advisory.

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X13 · Undrained process stream10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a child process that has BOTH standard streams redirected drains both — reading one to the end while the other is never read deadlocks once the child fills the unread pipe.

Method: Roslyn syntax + semantics: ProcessStartInfo launches with both streams redirected, checked for a drain of each stream across the enclosing type. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `spawn` imported from `child_process` whose stdout and stderr are both pipes (no options, no `stdio`, or `stdio` of `'pipe'`), bound to a local that never leaves its scope, where exactly one of the two streams is read, the other never, and the child’s `close`/`exit` (or the read stream’s end) is awaited; a shell redirect in the call’s arguments or a `kill` of the child suppresses it. The same rule reads Python’s `subprocess.Popen`, Dart’s `Process.start`, Ruby’s `Open3.popen3`, and Scala’s JDK process starts (`new ProcessBuilder(…).start()` with no `redirectErrorStream`/`redirectError`/`redirectOutput`/`inheritIO`, `Runtime.getRuntime.exec`) where one of `getInputStream`/`getErrorStream` is read and the other never while `waitFor()` is called or the read stream is read to its end. Deterministic, provable per finding. Advisory.

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X14 · Bypassable address classification10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether a hand-rolled public/private IP check can be walked past — a method that unwraps IPv4-mapped IPv6 but returns the opposite verdict for the same host written as IPv4-compatible, 6to4 or NAT64.

Method: Roslyn syntax + semantics: methods that unwrap IPv4-mapped IPv6 and hand-roll IPv4 range carve-outs, checked for whether the IPv6 branch also accounts for the IPv4-compatible, 6to4 and NAT64 embeddings. Deterministic, provable per finding. Advisory.

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X15 · Unvalidated length from an untrusted reader2.2 / 10Critical✓ Tool-verified

Other · Security — Whether a length read out of the stream being parsed is bounded before it is allocated or read — an unchecked count taken from the input lets the input choose the allocation.

Method: Roslyn syntax + semantics: integer lengths read from a BinaryReader and spent on a bulk read or an array allocation, checked for any comparison or bounding call on the value anywhere in the method. Deterministic, provable per finding. Advisory.

`numberOfBitmaps` is read from the bytes being parsed at line 580 (`getInt`), then used to size an `Array.fill` at line 585 — and nowhere in its scope is `numberOfBitmaps` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `numberOfBitmaps` against the bytes actually remaining and a maximum the format allows before allocating. — spark/src/main/scala/org/apache/spark/sql/delta/deletionvectors/RoaringBitmapArray.scala:585
`numberOfBitmaps` is read from the bytes being parsed at line 159 (`getInt`), then used to size a `new RoaringBitmap[]` at line 164 — and nowhere in its scope is `numberOfBitmaps` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `numberOfBitmaps` against the bytes actually remaining and a maximum the format allows before allocating. — kernel/kernel-api/src/main/java/io/delta/kernel/internal/deletionvectors/RoaringBitmapArray.java:164
`length` is read from the bytes being parsed at line 118 (`readInt`), then used to size a `new byte[]` at line 139 — and nowhere in its scope is `length` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `length` against the bytes actually remaining and a maximum the format allows before allocating. — flink/src/main/java/io/delta/flink/kernel/dv/BinDVAccess.java:139

What to do

Each finding names the read that takes the length from the input and the site that spends it, and states that the value is never compared in between. Confirm from the two, then bound the length against the remaining stream before using it.

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X16 · Unfloored truncation loop10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a loop that shortens a string until it fits a length budget has a floor — one with none grinds the value down to the empty string, or past it into a negative-length `Substring`.

Method: Roslyn syntax + semantics: while/do loops whose body's only effect on a string is to drop its last character, checked for whether anything — a direct comparison on the length, a body guard, a break — bounds that length below. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `while`/`do` loop whose body’s one assignment to a value is `x = x.slice(0, -1)` or `x = x.slice|substring|substr(0, x.length - 1)`, driven by a condition that reads `x.length` only as a term of a larger expression — never compared directly, never tested for truthiness, and with no other read of `x` — and whose body has no `break`, `return`, `throw` or `if` naming `x`. Deterministic, provable per finding. Advisory.

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X17 · Uncapped recursion over a caller-supplied document3.5 / 10Weak✓ Tool-verified

Other · Security — Whether a walk that recurses through a JSON/XML tree handed in by its caller bounds how deep it will go — an uncapped walk lets the document's nesting choose the stack depth, and the resulting StackOverflowException cannot be caught.

Method: Roslyn syntax + semantics: methods that take a JSON/XML document node and call themselves with a child of it, reachable from an externally-callable member of the same type that accepts a document, checked for any depth parameter, descent counter or threaded arithmetic anywhere in the walk. On a repository with no .NET source it reads TypeScript off the engine’s own token stream (test, vendored, generated and minified paths and `.d.ts` not) with the same rule: a function or method with a parameter typed as a document value — `unknown`, `any`, `object`, `Record<string, unknown|any>`, a JSON alias (`JsonValue`, `JSONObject`, …) or a DOM node global the file does not rebind — that calls itself (bare, or through `this` for a method, or hands itself to a call over the value as in `value.map(walk)`) with something it took out of that value and never through an ancestor accessor such as `closest()` or `parentElement`, that is exported or reached from an exported function (a public method of the same exported class) taking such a value, and that names no depth, level, nesting, recursion, remaining or budget anywhere and threads no `+`/`-` arithmetic through a self-call. Plain JavaScript is not read: with no annotation nothing tells a parsed document from a tree the code built itself. Deterministic, provable per finding. Advisory.

`LastCheckpointInfo.treeNodeToChecksum` is public, takes a document from its caller (line 256) and hands it to `traverseJsonNode`, which calls itself at line 264 with a piece of `currentNode` (and at line 270), not as a tail call the compiler turns into a loop — and nowhere in `traverseJsonNode` is there a depth parameter, a descent counter, or any other cap. The walk therefore spends one stack frame per LEVEL of the value it is handed, so the nesting of the caller's document — not this code — decides how deep the stack goes. On the JVM's default 1 MB thread stack a walk like this one throws `StackOverflowError` from about 500–2,000 levels on a cold first call and 6,000–17,000 once warmed up (OpenJDK 21 and 25), while `ujson.read`, Jackson's `readTree` before 2.15 and circe before 0.14.16 accept any nesting (2,000,000 levels from 4 MB) and circe 0.14.16 accepts 4,096 — on a cold JVM even play-json's cap of 1,000 is past the point the walk fails. `StackOverflowError` is not `NonFatal`: `Try`, `case NonFatal(e)` and `recover` do not stop it, and in a `Future` on the global execution context it leaves the future forever incomplete. Thread a depth argument through `traverseJsonNode` and reject the value past a fixed maximum, or rewrite the descent with an explicit stack. — spark/src/main/scala/org/apache/spark/sql/delta/LastCheckpointInfo.scala:264

What to do

Each finding names the externally-callable member that accepts the document and the self-call that descends, and states that no depth parameter or counter exists anywhere in the walk. Confirm from the two, then thread a depth argument through the walk and reject documents past a fixed maximum, or rewrite it with an explicit stack.

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X18 · Disposal-pattern correctness7.1 / 10Strong✓ Tool-verified

Other · Code Health — Whether a type's disposal matches what it OWNS — releasing what it created, leaving alone what it was handed, and not declaring a finalizer for state that has nothing unmanaged to finalize.

Method: Roslyn syntax + semantics: every assignment to a disposable field is read to decide whether the type CREATED the value or was handed it, and the type's disposal is checked against that answer — an injected interface it disposes, a value it constructed and never releases, a finalizer on a type holding nothing unmanaged, and a disposable local whose every reference is a plain member read. A value handed to a container that disposes its contents (a parent control's `Controls` collection, a component `IContainer`) is released by that container and is not reported; generated code is out of population. On a repository with no .NET source the same ownership questions are read in JavaScript/TypeScript off the engine’s own token stream (test, vendored, generated and minified paths not): a class declaring `dispose()`, `[Symbol.dispose]()` or `[Symbol.asyncDispose]()` that disposes a field it was handed through a constructor parameter typed as a repository interface or resolved by a dependency-injection container; that assigns a field only ever from `new X(…)` of a disposable class and neither releases it anywhere in the class nor names it in its disposal member or a method that member calls, nor hands it to anything else; and a `const`/`let` local built from literals only whose every reference opens a statement operating on a non-release member of it. A class is disposable when every repository declaration of its name declares or inherits a disposal member, or when it is a documented library disposable (`vscode` EventEmitter, CancellationTokenSource and Disposable; three.js geometries, materials, textures, render targets, renderers, controls and composers). The finalizer arm has no JavaScript counterpart: a class cannot declare one. Dart is read for the owned-and-never-released arm: a Flutter `State` (or a class declaring `dispose()`/`close()`) whose library-private field is written only with direct creations of a framework controller, `FocusNode`, `StreamController` or periodic `Timer` (or a `.listen(…)` into a field declared `StreamSubscription`), which nothing in the class or its library releases (`dispose`/`close`/`cancel`) and which is never handed on except as a named argument. Ruby is read for the owned-and-never-released arm and the abandoned-local arm: a class declaring an instance `close`, `dispose`, `shutdown`, `stop`, `disconnect` or `terminate` whose instance variable is written only with a blockless core descriptor creation (`File.open`/`new`, `Tempfile`, `Dir.open`, `IO.popen`, the `socket` and `openssl` socket classes) that no method of the class closes and that is never handed on (passed, returned, stored, exposed by `attr_reader`, delegated) — a class whose superclass or mixin lies outside the repository is not judged — and a blockless creation read through and dropped (`File.open(path).read`) or held in a local that is never closed, returned, passed or stored (a `&:read` block-pass, an `autoclose: false` borrow and a `fileno` hand-over are not abandonment). PHP is read for the same two arms: a class (not a trait, and not one using a trait) declaring an instance `close`, `dispose`, `shutdown`, `stop`, `disconnect` or `terminate` whose `private` property (or a `final` class's `protected` one) is written only with a direct core `fopen`, `tmpfile`, `popen`, `proc_open`, `fsockopen`, `stream_socket_client`/`server` or `opendir` that nothing in the class closes (`fclose`, `pclose`, `closedir`, `unset`, a reset to `null`) and that is never handed on, and a handle held in a function's local, or read through as the argument of a reader, that is never closed, returned, passed, captured or stored; a `php://` stream, `curl_init`, `SplFileObject`, `PDO` and a function the repository declares under the core name are not read. Deterministic, provable per finding. Advisory.

`Files.walk(…)` opens something that has to be given back — a file descriptor, a socket, a directory handle — and its only use reads `.iterator` through it and drops it, so this expression both creates the value and is the last place that can release it, and does not. Every call leaks one more open handle until the collector happens to reach it: `Too many open files` under load, and on Windows a file that cannot be replaced or deleted while it is held. Open it with `scala.util.Using.resource(Files.walk(…)) { r => … }`, which releases it on every path including a throw, or hold it and call `.close()` in a `finally`. — spark/delta-suite-generator/src/main/scala/io/delta/suitegenerator/SuitesWriter.scala:123

What to do

Each finding names the value and the span that decides who owns it — the `new` that created it, or the constructor parameter that handed it over. Confirm ownership from that span, then make the disposal match it: release what this type created, leave what it was injected with to whoever created THAT, and drop a finalizer whose type holds nothing unmanaged to release.

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X19 · Unrestored process-global state10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a method that temporarily changes state belonging to the whole process — the working directory, an environment variable — puts it back on EVERY path: a restore reached only when nothing throws leaks the change to the rest of the process.

Method: Roslyn syntax + semantics: method bodies that write the process working directory or an environment variable and write it back in the same body, checked for whether that restore sits in a `finally`/`catch` or only on the straight-line path. On a repository with no .NET source the same rule reads production JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not): `process.chdir`, `process.env.NAME =`/`["NAME"] =` and `delete process.env.NAME`, and Deno’s `Deno.chdir`/`Deno.env.set`/`Deno.env.delete`, paired per function body (a nested function or arrow is its own body, and module top-level code is none), where the last write puts back a local the body captured from the same global or deletes a variable the first write set, with at least one statement between them; a write in a `catch`/`finally` of that body silences it. Deterministic, provable per finding. Advisory.

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X20 · Mistyped argument guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether an argument guard throws the exception its own condition describes — a guard that rejects a value for being EMPTY and reports it as `NullPointerException` (Java, Kotlin, Scala), `ArgumentError.notNull` (Dart) or `ArgumentNullException` (F#'s `nullArg`) tells the caller a parameter was null when it provably was not.

Method: Roslyn syntax: `throw new ArgumentNullException(nameof(p))` statements controlled by an `if`, whose condition is read for a test that is true of a NON-null `p` — an emptiness test that dereferences it (`p.Count == 0`, `!p.Any()`) or a BCL predicate documented true of the empty value (`string.IsNullOrEmpty(p)`). Deterministic, provable per finding. Advisory.

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X21 · Side-effecting pattern guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a `when` guard is free of side effects — a guard that increments a counter or assigns while deciding whether its arm matches applies that change during PATTERN MATCHING, on an arm that may not be selected, and skips it entirely when a short-circuit to its left answers first.

Method: Roslyn syntax: `when` guards on case labels and switch-expression arms, read for a mutation (`++`/`--`/assignment) sitting in a position the guard's own `&&`/`||`/`??`/`?:`/`?.` can skip. Deterministic, provable per finding. Advisory.

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X22 · Contradicted release guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a method that TAKES a lock or semaphore and gives it back from a flag-guarded `finally` returns the value that flag implies — reporting success while the guard hands the primitive back admits a second caller the exclusion was there to keep out, and reporting failure while the guard keeps it leaves nothing to ever give it back.

Method: Roslyn syntax: `try` statements whose `finally` releases a synchronisation primitive under a bare local-bool guard, where the method also TOOK that same primitive before the `try`, checked for a `return` of a bool literal whose value disagrees with the flag state the method's own straight-line assignments put it in. Deterministic, provable per finding. Advisory.

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X23 · Unguarded diagnostic materialisation6.8 / 10Adequate✓ Tool-verified

Other · Code Health — Whether the work a diagnostic log line costs is paid only when that line is wanted — C# evaluates a call's arguments BEFORE the call, so a trace/debug message joined or projected out of a collection is built in full on every pass, and then discarded by a sink the shipped configuration leaves switched off.

Method: Roslyn syntax: log calls at a diagnostic level (a `Log`-prefixed method naming Trace/Debug/Verbose, or a bare `Debug`/`Trace`/`Verbose` on a receiver named for a logger), whose argument list is read for a call whose cost scales with a sequence — a LINQ operator, a materialisation, `string.Join`, a serializer — with no enclosing level check or conditional-compilation region. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `debug`/`trace`/`verbose` call on a receiver named for a logger, or a `log`-prefixed method naming the level, whose argument calls an array operator (`map`/`filter`/`reduce`/`sort`/…), `Array.from`, `Object.keys/values/entries`, `JSON.stringify`/`util.inspect` over anything but a literal, or an array `join` — outside any arrow or function passed as an argument, which the logger calls only when the level is on — with no enclosing `if`, `&&` or `?:` whose condition names a level, a level string, or the `NODE_ENV`/`__DEV__`/`DEV` build switch. Deterministic, provable per finding. Advisory.

`debug` at line 101 is called with an argument built by `Arrays.toString(conf.getPrimaryKeyOrdinals())` (line 104), whose cost grows with the collection it walks. Java evaluates a call's arguments BEFORE entering the method, so that join/projection runs in full every time this line is reached — and then the level check inside the logger discards the string it produced, because debug is a level a shipped configuration normally leaves off. Nothing here decides beforehand whether the message is wanted: no `isDebugEnabled`/`isTraceEnabled` test, no debug flag, no lambda or `Supplier` the logger calls only when the level is on. — flink/src/main/java/io/delta/flink/sink/DeltaSinkWriter.java:101

What to do

In Java, put the construction behind the logger's own check (`if (log.isDebugEnabled())` for SLF4J and Log4j, `if (logger.isLoggable(Level.FINE))` for java.util.logging), or hand the logger a lambda it calls only when the level is on (Log4j 2's `Supplier` overloads, SLF4J 2's `log.atDebug().addArgument(() -> …)`). A `{}` placeholder alone is not the fix: it defers the formatting, not the stream, join or serialisation in the argument.

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X24 · Document value interpolated into markup unescaped10.0 / 10Exemplary○ Nothing flagged

Other · Security — Whether text read out of the document being converted is escaped before it is written into generated markup — a value the document's author chose, interpolated into an attribute the surrounding literal delimits, can close that attribute and open another.

Method: Roslyn semantic model over the whole compilation: a string-typed `Value`/`InnerText`/`InnerXml`/`Text` member declared inside `DocumentFormat.OpenXml` or `System.Xml` is a taint SOURCE, propagated through assignments, returns, arguments, tuple elements and string composition to its transitive closure, then read at interpolated-string holes that sit in a markup position the surrounding literal itself delimits. Escaper/encoder calls and enclosing validator conditions cut the flow. Flow- and container-insensitive by construction. A second arm needs no provenance at all and reports a type that CONTRADICTS ITSELF — the same expression escaped at one delimited markup hole and interpolated raw at another hole in the same markup position of the same type, which the type's own escaping proves is a defect without knowing where the value came from. On a repository with no .NET source it reads JavaScript/TypeScript off the token stream with the same rule: a DOM read of raw document text (`getAttribute`, `textContent`, `innerText`, `nodeValue`) is the source, propagated through local bindings and string composition, and judged at template-literal and concatenation holes in the same two delimited markup positions; escapers and validating conditions cut it, and documentation-site, test, vendored and minified scripts are not read. Deterministic, provable per finding. Advisory.

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X25 · Inert configuration knob10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a value the caller is invited to supply is the value the type actually uses — a constructor parameter stored in a private field that nothing ever reads while the default it was given is spelled out a second time at the site that should have read it, a keyed lookup that falls back to a different setting than the one its key names while the same type falls back to the matching one for that same key, or a culture-sensitive parse given no format provider by a type that feeds its own settable culture to the same kind of parse elsewhere, or a number an entry point writes to standard output under the host's culture while the same entry point formats with the invariant culture elsewhere. Either way, every caller who supplies a value silently gets something else.

Method: Roslyn syntax: private instance fields of a non-partial type assigned in a constructor from one of its own parameters with a `??` fallback, checked for whether anything in the type body reads the field and whether that same fallback expression is spelled out again outside the constructor; and `??` fallbacks onto a member access from a lookup call carrying exactly one string literal, grouped by that key across the type and checked for a fallback member whose folded name disagrees with the key while a sibling site for the same key agrees with it. On a repository with no .NET source the first two arms read JavaScript/TypeScript off the engine’s own token stream (tests included, bundles and vendored paths not): a `#x`, `private` or `private` parameter-property instance field filled in the constructor from a parameter (or one member of one) through `??`/`||` or a parameter default, never read anywhere in the file by name, whose constructed default is spelled again in the class body; and `lookup("key") ?? s.member` grouped by key per class, or per module outside every class. The culture arm has no JavaScript counterpart: its parses take no locale. Deterministic, provable per finding. Advisory.

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X26 · Unsynchronised callback handoff10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a value handed from a callback to the body that waits on it crosses on something built to be crossed — a `Queue<T>`/`List<T>`/`Dictionary<K,V>` written inside an event handler and read back outside it is mutated by two flows at once, and the semaphore or completion source beside it orders how MANY items exist while leaving the collection's own head, tail and backing array unprotected.

Method: Roslyn syntax: method, accessor, local-function and lambda bodies that declare BOTH a non-thread-safe generic collection (`Queue`/`Stack`/`List`/`Dictionary`/`HashSet`/`Sorted*`/`LinkedList`) and a synchronisation primitive (`SemaphoreSlim`/`TaskCompletionSource`/`ManualResetEvent(Slim)`/`AutoResetEvent`/`CountdownEvent`) as locals, then read for a `+=`-registered lambda that raises that primitive while the body outside every lambda waits on it — and, in that scope, a mutating call on the collection inside the lambda paired with a mention of it outside. Any `lock` in the scope abstains it. On a repository with no .NET source the same handoff is read in Java off the engine’s own token stream (test source sets, vendored and demonstration paths not): an `ArrayList`/`LinkedList`/`ArrayDeque`/`PriorityQueue`/`Hash*`/`LinkedHash*`/`Tree*` local and a `CountDownLatch`/`Semaphore`/`CompletableFuture` local, a lambda or anonymous class that raises the primitive and mutates the collection, and a wait outside it; any `synchronized` or `lock()` abstains the body. Because each of those primitives orders what the callback wrote before raising it, only a touch that provably overlaps the callback is convicted: one after the registration and before the next wait, or one in a loop registered-before, waiting on every pass and not declaring the collection. Deterministic, provable per finding. Advisory.

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X27 · Collection changed while being enumerated10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether an enhanced `for` leaves the collection it is walking alone — a body that adds to or removes from the very collection the loop is iterating invalidates the fail-fast iterator it is holding, so the next `next()` throws `ConcurrentModificationException` and the remaining elements are never seen. Whether a `for` loop leaves the `dict`, `set` or `deque` it is walking alone — CPython's iterators over those check that the collection has not changed size since the loop began, so a body that removes from (or empties) the very collection the loop is walking makes the next step raise `RuntimeError: dictionary changed size during iteration` and the remaining items are never seen. Whether a `for` comprehension or `foreach` leaves the mutable collection it is walking alone — an `ArrayBuffer` or `ListBuffer` counts its changes and its iterator checks the count, an `ArrayDeque` (and `mutable.Queue`/`mutable.Stack`) is walked by index up to its starting length, and a `java.util` collection walked through `asScala` is fail-fast, so a body that adds to or removes from the very collection the loop is walking makes a later step throw `ConcurrentModificationException` (`IndexOutOfBoundsException` for a deque) and the remaining elements are never seen.

Method: Roslyn syntax + semantics: `foreach` statements whose body calls a structural mutator (`Add`/`Remove`/`Clear`/`Insert`/…) on the very expression the loop is enumerating. Two arms. ARM A — the source is a concrete fragile BCL collection, or a live `Keys`/`Values` view over one, and the mutator resolves to that same collection's own member; concurrent and immutable collections and arrays are outside the population by construction, since their enumerators survive a structural change. ARM B — the source is an argument-less accessor CALL on a receiver whose body is in source: the accessor must return a stored field VERBATIM and a sibling member must structurally change that same field, both read off the implementations rather than from the members' names. A mutation the loop provably exits immediately after (`break`/`return`/`throw`/`goto`), or one written inside a nested loop or a lambda, is counted and never reported. Deterministic, provable per finding. Advisory.

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X28 · Index access outside its own emptiness guard10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a condition that tests a value for emptiness indexes that same value only where the test holds — an `||` written one parenthesis too far to the left leaves an index access outside the guard beside it, so the empty case the guard exists to anticipate reaches the index and throws.

Method: Roslyn syntax only, no semantic model: the OUTERMOST `&&`/`||` of every boolean condition, read for a symbol the condition tests for emptiness (`string.IsNullOrEmpty`/`IsNullOrWhiteSpace`, a `Length`/`Count` comparison against a literal, `Any()`, a `Length`/`Count` pattern, or a comparison against `""`) and ALSO indexes. Each `symbol[...]` access is placed by a boolean-reachability walk from the access up to the outermost connective: an access is COVERED when some enclosing step has it in the right operand and the left operand, under the truth value that step forces, proves the symbol non-empty — a recursion over `&&`/`||` whose true- and false-directions are asymmetric. A finding needs BOTH an uncovered access and a covered one on the same symbol in the same condition, which is the agreeing twin that separates a misplaced parenthesis from an unrelated length test. Bare index accesses with no emptiness test in the condition are neither counted nor reported; a non-identifier receiver and a lambda nested inside the condition are outside the population. Deterministic, provable per finding. Advisory.

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X29 · Per-element action decided by a fixed element10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a decision taken once per element is taken ABOUT that element — a test inside a counted loop that reads a fixed subscript of the very collection its guarded statement indexes by the loop variable applies element zero's answer to all of them, so the elements that differ from it are all handled wrongly, and in the same direction.

Method: Roslyn syntax only, no semantic model: every `for` statement declaring exactly ONE loop variable, and every `if` inside its body that is not under a nested loop or a lambda. A site enters the population when the `if`’s condition never mentions the loop variable while the statement it guards indexes some collection by that variable ALONE (`c[i]`; `c[i + 1]` and `c[i, j]` are outside it). A finding additionally needs the AGREEING TWIN at the same-collection grain: the condition must read THAT SAME collection at a subscript that does not move — written into the condition, or reached through a local declared BEFORE the loop, so an alias bound inside the body is not followed. Both collection expressions must be simple identifiers. On a repository with no .NET source the same rule reads JavaScript/TypeScript off the engine’s own token stream (tests included, bundles and vendored paths not): a `for (let|var|const x = …; …; …)` with one declarator and a braced body, an alias followed only when it is declared before the loop in a block that encloses it and never assigned inside the loop. Deterministic, provable per finding. Advisory.

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X3 · Exception handling7.3 / 10Strong✓ Tool-verified

Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.

Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.

`case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. (×7) — spark/src/main/scala-shims/spark-4.1-4.3/VariantShreddingShims.scala:59, spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:131, spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:169, …
An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it. (×5) — spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:1417, spark/src/main/scala/org/apache/spark/sql/delta/RowIndexFilterMetadataColumnUtils.scala:181, spark/src/main/scala/io/delta/sql/AbstractDeltaSparkSessionExtension.scala:149, …
`case _` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. (×2) — spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala:370, spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala:436
`case e: Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. — spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:92
`case _: Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. — iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/IcebergRESTCatalogPlanningClient.scala:265
`catch (Exception)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter. (×2) — flink/src/main/java/io/delta/flink/table/AbstractKernelTable.java:466, flink/src/main/java/io/delta/flink/table/CatalogManagedTable.java:175

What to do

Swallowed exception (caught, then discarded)

Do you agree with this assessment?

X30 · Support guard that admits what it rejects10.0 / 10Exemplary○ Nothing flagged

Other · Code Health — Whether a guard written as a NEGATED `||` says what its author meant — `!(a || b || x != k)` is `!a && !b && x == k` by De Morgan, so a bail-out that mixes capabilities the code needs with a fault it refuses turns inside out: it fires only where the capabilities are ABSENT, and lets every value the fault term names walk straight into the body that cannot handle it.

Method: Roslyn syntax only, no semantic model: every logical-not whose operand is a parenthesised `||` chain of two or more disjuncts, flattened (a left-nested `a || b || c` read once would see `(a || b)` as one disjunct). A site enters the population on that shape alone. A finding additionally needs the disjuncts to DISAGREE in polarity: at least one bare boolean read — an identifier or member access, never an invocation, which is a predicate rather than a capability flag — and at least one `x != <constant>`, the only form that negates into an exact-value pin (`== null` negates into a looser requirement and is outside the fault set). Consistently-polarised disjunctions, all-fault or all-capability, are counted and never reported; a negated `&&` is outside the population entirely. No same-receiver gate: it was measured to cost a real defect and remove no false positive. Deterministic, provable per finding. Advisory.

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X4 · Structured logging7.1 / 10Strong✓ Tool-verified

Other · Code Health — Whether log calls use message templates (queryable) rather than interpolated strings.

Method: Roslyn syntax scan: every log call-site counted; interpolated-string first-argument violations flagged. Population is all log calls, not estimated. On a repository with no .NET source it reads JavaScript/TypeScript off the engine’s own token stream (test, vendored and minified paths not) with the same rule: a `trace`/`debug`/`info`/`warn`/`error`/`fatal`/`verbose`/`silly`/`http`/`log` call on a receiver named for a logger, in a package whose own or an enclosing `package.json` declares a logger that carries values as fields (pino, pino-http, nestjs-pino, Fastify, winston, bunyan, tslog, LogTape, roarr), whose first deciding argument is a template literal with substitutions; an object-literal fields argument is stepped over, a plain string message clears the call. Python is read the same way: a `debug`/`info`/`warning`/`error`/`exception`/`critical`/`log` call on a logger in a file that imports the standard library’s `logging` or structlog (loguru, which formats at the call, is not judged), whose message is a whole f-string with a non-constant field; a `%`-formatted, `.format()`-ed or concatenated message is not convicted, as in C#. PHP is read the same way: a PSR-3 level call (`emergency`…`debug`, `log`) on a logger (`$logger`, `$this->logger`, Laravel’s `Log::`, `logger()`, `\Drupal::logger()`) in a package whose `composer.json` requires a PSR-3 logger or a framework that hands one out (psr/log, Monolog, Laravel, Symfony, Drupal, CakePHP), or a file that imports one, whose message is a double-quoted string interpolating a variable; a single-quoted message clears the call, and `sprintf` or `.` concatenation is not convicted, as in C#. Dart is read the same way: a `trace`/`debug`/`info`/`warn`/`error`/`fatal` call on Sentry’s structured logger (`Sentry.logger`) whose message is a whole string literal interpolating a value (`$name`, `${…}`); the `Sentry.logger.fmt` template API clears the call. Dart that logs only through loggers with one message and no fields (package:logging, package:logger, talker, dart:developer) is not applicable rather than a reach gap. Ruby is read the same way: a `trace`/`debug`/`info`/`warn`/`error`/`fatal` call on the console gem’s `Console` (declared by a Gemfile, gemspec or Gemfile.lock, or required) or, where SemanticLogger, Ougai or dry-logger is declared or required, on a receiver named for a logger (`logger`, `@logger`, `Rails.logger`, `log`), whose first deciding argument is, as the whole argument, a double-quoted string interpolating a non-constant value (`#{…}`, `#@ivar`); a plain literal clears the call, keyword arguments are the fields, and a block, `%`-format or `+` concatenation is not convicted. Ruby that logs only through the standard Logger (Rails.logger) is not applicable rather than a reach gap. Deterministic.

`debug` at line 170 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.debug("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:170
`info` at line 366 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:366
`warn` at line 387 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.warn("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:387
`info` at line 519 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:519
`info` at line 602 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:602
`warn` at line 624 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.warn("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:624
`info` at line 355 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:355
`info` at line 197 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text. — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetBatchRowReader.java:197

What to do

Interpolated log message defeats structured logging

Do you agree with this assessment?

X5 · Nullable reference types2.0 / 10Critical✓ Tool-verified

Other · Code Health — Whether Scala's null is held to the type system and not undermined by assertions — a file compiled with `-Yexplicit-nulls` is one where `String` excludes null and `String | Null` admits it, a file under WartRemover's `Null` wart or Scalafix's `DisableSyntax.noNulls` is one whose code cannot write `null` and must say `Option`, and each `.nn`, `import scala.language.unsafeNulls` or null-lint suppression is the author overruling that.

Method: Roslyn compiler-options scan: NullableContextOptions per project; null-forgiving (!) suppression density per 1k syntax nodes. Deterministic, adoption plus suppression penalty.

No build over this repository's 502 Scala product file(s) passes `-Yexplicit-nulls`, enables WartRemover's `Null` wart or runs Scalafix's `DisableSyntax.noNulls`, so every reference type admits null and nothing reports a `null` written into the code or returned from a Java API — the first one to reach a method call is a `NullPointerException`. `Option` by convention is a habit no tool here holds the code to.

What to do

On Scala 3, add `-Yexplicit-nulls` to `scalacOptions` so `String` and `String | Null` mean different things, and type each Java API's result as nullable where it can return null; on Scala 2 (or as a first step), enable WartRemover's `Null` wart (`wartremoverErrors += Wart.Null`) or Scalafix's `DisableSyntax.noNulls = true` so the code holds absence in `Option`. Then pay the assertions down rather than adding to them: each `.nn` is a null the compiler could not rule out — wrap the Java value in `Option(…)` at the boundary, pattern-match on `null` once there, or change the API so the null cannot arrive; an `unsafeNulls` import switches the checking off for everything after it.

Do you agree with this assessment?

Reference — by lens

The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.

Lens	Score	Rating	Impact
Code Health	62%	Adequate — gated by X5	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Architecture	87%	Adequate — gated by D26	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Maturity	71%	Strong	Solid.
Readiness	62%	Adequate	Acceptable, with room to improve.
Security	77%	Adequate — gated by D29	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Performance	78%	Strong	Strongest area.

Unscored — 3 check(s) recorded observations but carry no score

These checks ran and found something, but they do not carry a score — either by design (an advisory check reports evidence rather than grading it) or because they could not be scored here. They are excluded from the score for that reason, not because there was nothing to see.

P12 CI test-gate honesty — 1 observation(s) recorded · Reported, not scored — this card publishes what the CI gate does with the test inventory rather than grading it. The findings above are its output.
X10 Duplicated predicate — 25 observation(s) recorded · Advisory — this card reports evidence and never carries a score.
X7 Silent fallback defaults — 3 observation(s) recorded · Advisory — this card reports evidence and never carries a score.

Not evidenced — 3 control(s) we could not find positive evidence for

These checks grade a working control, and the repository shows no evidence of one. That is deliberately not scored as a zero: a repository cannot show an ops runbook, a database TTL or an infrastructure-side audit log, so absence of evidence here is not evidence the control is missing. It is also not a statement that the check is irrelevant to this codebase — the thing it grades applies; we just could not see it. Excluded from the score either way.

C3 Audit Trail — Not assessed: these audit controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks audit controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C4 Data Retention — Not assessed: these retention controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks retention controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C5 Data-Subject Rights — Not assessed: these data-subject rights controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks data-subject rights controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.

Not included — 46 check(s) not relevant to this codebase

These checks had nothing to measure here (no tests, no git history, the codebase is small, or the architecture style doesn't apply), so they're omitted above rather than scored low.

AC1 Text alternatives — No web markup found — accessibility is not applicable to this repository.
AC2 Forms & labels — No web markup found — accessibility is not applicable to this repository.
AC3 Page structure — No web markup found — accessibility is not applicable to this repository.
AC4 Keyboard semantics — No web markup found — accessibility is not applicable to this repository.
AC5 ARIA correctness — No web markup found — accessibility is not applicable to this repository.
AC6 Visual & motion safety — No web markup found — accessibility is not applicable to this repository.
AC7 A11y enforcement — No web markup found — accessibility is not applicable to this repository.
AX1 Captive dependencies — Not applicable: this repository's Java imports no dependency-injection container and defines no container of its own — nothing that both registers and resolves bindings, and nothing that names two lifetimes — so nothing holds one lifetime's instance while handing out another's; this repository's Python imports no dependency-injection container and defines no container of its own — nothing that both registers and resolves bindings, and nothing that names two lifetimes — so nothing holds one lifetime's instance while handing out another's; this repository's Scala imports no dependency-injection container and defines no container of its own — nothing that both registers and resolves bindings, and nothing that names two lifetimes — so nothing holds one lifetime's instance while handing out another's.
AX2 Stateful singletons — No container singleton was found, so there is no shared instance for concurrent requests to race on. No class in this Java code is a Spring, JSR-330 or CDI singleton bean. No function in this Python code is served by a threaded web framework (a Flask, Bottle or FastAPI route, a Django or Pyramid view), so no module is shared between request threads. No class in this Scala code is a Play controller, a Cask routes object, a Scalatra servlet, a Finatra controller, an Akka/Pekko HTTP routes holder or a JSR-330/Spring singleton, so no instance is shared between request threads. TypeScript/JavaScript runs each process's requests on one event loop, so no two requests write a shared object at the same instant (interleaving across an await is a different defect).
AX5 Architecture & structure — not assessed — architecture style/structure is computed from a project graph (projects, types, module namespaces) that was not loaded for this repository, because the repository is written in a language this check does not yet model, or because its projects failed to load. This is a gap in the analyzer, not a finding about this repository
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — no test/production split to check
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
AXB2 Runtime readiness — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
AXR1 Runtime accessibility — compose up failed (exit 18 — an image could not be pulled) — taskmanager2 Pulling taskmanager Pulling jobmanager Pulling jobmanager Error Get "https://registry-1.docker.io/v2/": Forbidden taskmanager Error context canceled taskmanager2 Error context canceled Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the earlier `compose pull` step reported: taskmanager2 Skipped - Image is already being pulled by taskmanager jobmanager Skipped - Image is already being pulled by taskmanager taskmanager Pulling taskmanager Error Get "https://registry-1.docker.io/v2/": Forbidden Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the runtime sandbox reaches registries only through the in-fence pull-through mirror, so an image the mirror does not carry cannot be fetched — this is a limit of our sandbox, not of your stack; runtime evidence skipped This is a statement about this run, not a statement about your application: nothing here says the surface is inaccessible, only that it was never rendered.
C1 Data Protection — Not assessed: these personal data controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks personal data controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
C2 Access Controls — Not assessed: these authorization controls are read from a source model (declarative annotations, request middleware, entity/column names, guard methods) that was not loaded for this repository — because the repository is written in a language this check does not yet model, or because its projects failed to load. Absence of an idiom this check recognises is NOT evidence that this repository lacks authorization controls: it may implement them entirely in its own ecosystem. This is a gap in the analyzer's language coverage, not a finding about this repository.
D10 Test Quality — ~349420 lines of test source are present (.py, .scala, .java) but no test cases reached the test census for this repository — no test root we could resolve declared them, or the files we read declare no cases in a test framework we recognise — so skipped/assertion-free tests couldn't be counted. Not scored — this is a gap in the analyzer, not a finding about this repository.
D11 Test Reliability — Test reliability not included
D12 Dependency Hygiene — Not scored — 1 Maven/Gradle manifest(s) were read, stating a version for 7 dependency(ies) and leaving 0 to a parent or an imported BOM, but no build resolved the dependency graph, so the outdated signal was not established. NOT a finding that these dependencies are current or healthy.
D18 Solution Shape — D18 scores the shape of a .NET solution; this repository has no .NET solution or project files, so the dimension does not apply.
D21 Naming Consistency — Naming consistency is measured on C# only; Java, JavaScript, Python, Scala, TypeScript not measured.
D22 Internal API Consistency — API consistency is measured on C# only; the exposed Python surface was not measured.
D23 Boundary Type-Coupling — No bounded-context organisation was detected either — neither a context-shaped layout, nor 2+ sibling source directories each declaring an aggregate root, nor 2+ projects each declaring an entity of their own. Declaring this codebase's bounded contexts (≥2) would let cross-boundary type coupling be assessed. Declare them in `.codehealth/config.yaml` at the repository root (create it if absent), mapping each context name to the module-path or namespace prefixes that belong to it — e.g. `architecture:` → `contexts:` → `Billing: ["src/billing", "Acme.Billing"]`, `Catalog: ["src/catalog", "Acme.Catalog"]`.
D24 Comment Value — D24 reads C# and Visual Basic comments only — this repository's production source is .java, .py, .scala, .ts, which was left unread. Not scored: this is a gap in the analyzer, not a verdict about this repository.
D25 ADR Conformance — None of 0 binding record(s) states a rule in checkable form (a backticked element with a prohibition, or an `adr-rules` block), so conformance cannot be read from the code. Write the rule as an `adr-rules` block (`forbid:` a symbol, a package or a dependency) to make it checkable.
D27 Navigability — D27 counts a call into the standard library or a dependency as unresolved for this repository's language (.scala), so too few call sites counted as resolved to assess navigability. Not scored: this is a gap in the analyzer, not a verdict about this repository.
D32 Data Compliance (PII/GDPR) — 2 file(s) were not parsed by semgrep — the PII/GDPR ruleset never ran over them
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D39 IL Efficiency — D39 measures the IL emitted by a .NET build; this repository has no .NET solution or project files, so the dimension does not apply.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D8 Code Coverage — Coverage not included — suite not readable by the collector
DM1 Domain Modelling — applicable but not scored (2 signals for this style, 2 needed — the count is met but a required primary signal is absent): 594 value object(s); 1 domain event(s); its domain events are published by services or handlers — no domain entity raises one
ED1 Event-Driven — not scored — this repository shows none of the 3 signals this lens looks for
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this lens looks for
P7 Outbound HTTP resilience — not applicable — no HTTP server, API framework or worker entry point was found in the JVM, JavaScript/TypeScript, Python source, so there is no service whose uptime a failing dependency could take down
P8 Schema migrations — no ORM, schema-migration tool or schema auto-create was found in this repository's dependency manifests or source, so there is no database schema for this check to judge
P9 Domain vs controller coverage — no coverage report found on disk — produce a coverage report in a standard format (`addSbtPlugin("org.scoverage" % "sbt-scoverage" % "<version>")` in `project/plugins.sbt`, then `sbt clean coverage test coverageReport`) and commit it — a hosted scan measures a clone of the repository, so a report that exists only in a working tree, a CI runner's or your own, never reaches it; the artefact is commonly gitignored, so `git add -f` that one file (or un-ignore its path) and commit it alongside the code it measures, or wire coverage collection into CI, to enable this cross-layer check
SC1 Supply-chain hygiene — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X2 Cancellation propagation — no C# was loaded; this repository's Scala, Java and Python were read, and no request in it can be cancelled by a caller — a Scala request takes no token: a Future cannot be cancelled, and cats-effect, ZIO and Monix interrupt the fiber that made the request from outside the call, not through a parameter; a Java request off Android takes no token: it is cancelled through the handle it returns (Future.cancel, Call.cancel, a Disposable), ambiently (io.grpc.Context) or by interrupting its thread, not through a parameter; a Python request takes no token: asyncio cancels the task and trio or anyio the scope that made it, from outside the call, and requests, httpx, aiohttp and gRPC take a timeout, not a cancellation
X32 Type resolved by simple name across every loaded assembly — This check is about how a .NET program searches the assemblies loaded into its process for a type, and this repository contains no .NET source, so there is nothing here for it to assess. Not a gap in the analyzer and not a finding about your code.
X6 Hand-rolled structured-format parsing — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.
X9 Subsumed condition operand — Advisory — this card reports evidence and never carries a score, so there is nothing missing here.

Appendix A — Findings (grouped)

The findings behind the scores, grouped by severity, then by dimension and kind. The high-severity issues are enumerated in full below; items per group are capped at 25 with any overflow stated explicitly per group, never silently truncated. The complete machine-readable list of every finding (all severities) is the companion findings.md in this report's bundle.

Critical — 25 finding(s)

D34 · Knowledge Freshness · Orphaned knowledge · ×8

Orphaned knowledge kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/LogSegment.java:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaMergeBuilder.scala:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/Protocol.java:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge spark/src/main/scala/org/apache/spark/sql/delta/deletionvectors/RoaringBitmapArray.scala:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge flink/src/main/java/io/delta/flink/kernel/CheckpointWriter.java:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge storage-s3-dynamodb/src/main/java/io/delta/storage/BaseExternalLogStore.java:1 — No living knowledge remains for this large file — its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.

D29 · Static Analysis (SAST) · REDACTED

REDACTED
REDACTED
REDACTED
REDACTED

D30 · Dependency Vulnerabilities · High CVE · ×4

REDACTED
REDACTED
REDACTED
REDACTED

D29 · Static Analysis (SAST) · REDACTED

REDACTED
REDACTED
REDACTED

D29 · Static Analysis (SAST) · REDACTED

REDACTED
REDACTED

AX3 · Project dependency cycles · Project dependency cycle · ×1

Project dependency cycle — The projects spark → sparkV1 → spark (one cycle inside a mutually-dependent group of 3 projects) form a reference cycle. Cyclic dependencies prevent independent build/test/deploy, blur ownership, and tend to grow into a big ball of mud. Break the cycle by extracting the shared types into a separate project both can reference.

D28 · Secrets (history) · REDACTED · ×1

REDACTED

D31 · IaC & Container Security · High IaC · ×1

REDACTED

D5 · Coupling · Circular dependency · ×1

Circular dependency — spark → sparkV1 → spark (one cycle inside a mutually-dependent group of 3 modules)

Serious — 904 finding(s)

D17 · Explicit Debt · TodoComment · ×354

TodoComment storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:317 — // TODO - raise exception? — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment storage/src/main/java/io/delta/storage/GCSLogStore.java:82 — // TODO Remove this hack when the GCS Hadoop connector fixes the issue. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark/src/main/scala/org/apache/spark/sql/delta/Checkpoints.scala:1582 — // TODO Remove this hack when the GCS Hadoop connector fixes the issue. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment storage/src/main/java/io/delta/storage/HDFSLogStore.java:129 — // TODO: this is a workaround of HADOOP-16255 - remove this when HADOOP-16255 is
TodoComment storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCRestClientPayload.java:180 — // TODO: Implement actual schema parsing logic based on schema format — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/DataFrameWriterV2WithV2ConnectorSuite.scala:52 — // Create operations - TODO: fix DeltaV2Table's name() to match DeltaTableV2 — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/ProtocolMetadataAdapterV2Suite.scala:44 — // TODO(delta-io/delta#5649): add type widening validation
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/test/DeltaV2SourceSuite.scala:175 — // TODO(#6232): DSv2 pins the table schema when the DataFrame is loaded, so restarting from a
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/test/DeltaV2SourceSuite.scala:209 — // TODO(#5900): fix exception mismatch
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/test/DeltaV2SourceSuite.scala:211 — // TODO(#5895): gracefully handle corrupt checkpoint
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/test/V2ForceTest.scala:64 — // TODO(#5754): Assert on test failure instead of ignoring
TodoComment spark-unified/src/test/scala/org/apache/spark/sql/delta/coordinatedcommits/CatalogManagedStreamingV2Suite.scala:43 — // TODO(#7140): Delta V2 supports catalog-managed reads but not catalog-managed
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaCacheTableTests.scala:118 — // TODO: ADD COLUMN is not properly supported in the STRICT V2 connector yet. The connector — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaCacheTableTests.scala:151 — // TODO: once [[DeltaV2Table]] implements [[Table.id]], the recreated table reports a new — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaJoinRefreshTests.scala:160 — // TODO: column mapping over Connect 4.2+ is flaky (the re-resolved read races between — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaJoinRefreshTests.scala:240 — // TODO: column mapping over Connect 4.2+ is flaky (the re-resolved read races between — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaJoinRefreshTests.scala:204 — // TODO: once [[DeltaV2Table]] implements [[Table.id]], the recreated table reports a — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaJoinRefreshTests.scala:216 — // table and nothing joins, in every classic mode. TODO: once [[DeltaV2Table]] implements — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaRepeatedAccessRefreshTests.scala:55 — // TODO: STRICT mode does not support schema evolution yet, so the wider INSERT fails with an — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaTempViewStoredPlanRefreshTests.scala:97 — // TODO: schema evolution is not fully supported in V2 STRICT yet, so the wider INSERT — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaTempViewStoredPlanRefreshTests.scala:142 — // STRICT: the view reads the filtered [1, 100]. TODO: the V2 STRICT ALTER COLUMN path — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaTempViewStoredPlanRefreshTests.scala:321 — // STRICT: the view reads the filtered [1, 100]. TODO: the V2 STRICT ALTER COLUMN path — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaTempViewStoredPlanRefreshTests.scala:377 — // STRICT: the view reads the filtered [1, 100]. TODO: the V2 STRICT ALTER COLUMN path — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-shared-tests/src/test/scala-shared/io/delta/tables/shared/DeltaTempViewStoredPlanRefreshTests.scala:435 — // TODO: the V2 STRICT ALTER COLUMN path reports the column as missing rather than — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment spark-connect/common/src/main/scala/org/apache/spark/sql/connect/delta/ImplicitProtoConversions.scala:32 — // TODO: Recursion limits — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
+ 329 more in this group — see findings.md.

D3 · God Classes · FileTooLong · ×42

FileTooLong: sources/DeltaSQLConf.scala spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSQLConf.scala — FileTooLong — 3475 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 2975 over it, 6.95× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: REDACTED REDACTED — FileTooLong — 3187 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 2687 over it, 6.37× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/OptimisticTransaction.scala spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala — FileTooLong — 2298 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 1798 over it, 4.60× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/SnapshotManagement.scala spark/src/main/scala/org/apache/spark/sql/delta/SnapshotManagement.scala — FileTooLong — 1282 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 782 over it, 2.56× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: actions/actions.scala spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala — FileTooLong — 1266 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 766 over it, 2.53× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: iceberg/TableMetadata.java icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java — FileTooLong — 1262 significant lines (blank, comment-only and punctuation-only lines excluded), about 97% of them inside a single declaration: TableMetadata (66-1963). The bar is 500 significant lines; this is 762 over it, 2.52× the bar. Moving the declarations that sit BESIDE it into sibling files will not shorten this file. Extract from INSIDE that declaration instead: lift each cohesive group of its body — the parts that share the same inputs and are named together — into its own unit in a sibling file, and have the original call them.
FileTooLong: read/DeltaV2MicroBatchStream.java spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java — FileTooLong — 1206 significant lines (blank, comment-only and punctuation-only lines excluded), about 93% of them inside a single declaration: DeltaV2MicroBatchStream (110-2133). The bar is 500 significant lines; this is 706 over it, 2.41× the bar. Moving the declarations that sit BESIDE it into sibling files will not shorten this file. Extract from INSIDE that declaration instead: lift each cohesive group of its body — the parts that share the same inputs and are named together — into its own unit in a sibling file, and have the original call them.
FileTooLong: schema/SchemaUtils.scala spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala — FileTooLong — 1080 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 580 over it, 2.16× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/Checkpoints.scala spark/src/main/scala/org/apache/spark/sql/delta/Checkpoints.scala — FileTooLong — 1061 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 561 over it, 2.12× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/ConflictChecker.scala spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala — FileTooLong — 974 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 474 over it, 1.95× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: catalog/AbstractDeltaCatalog.scala spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala — FileTooLong — 917 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 417 over it, 1.83× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/TableFeature.scala spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala — FileTooLong — 902 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 402 over it, 1.80× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/DeltaAnalysis.scala spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala — FileTooLong — 884 significant lines (blank, comment-only and punctuation-only lines excluded), about 83% of them inside a single declaration: DeltaAnalysis (84-1181). The bar is 500 significant lines; this is 384 over it, 1.77× the bar. Moving the declarations that sit BESIDE it into sibling files will not shorten this file. Extract from INSIDE that declaration instead: lift each cohesive group of its body — the parts that share the same inputs and are named together — into its own unit in a sibling file, and have the original call them.
FileTooLong: sources/DeltaSource.scala spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala — FileTooLong — 829 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 329 over it, 1.66× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: commands/alterDeltaTableCommands.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/alterDeltaTableCommands.scala — FileTooLong — 814 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 314 over it, 1.63× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/DeltaOperations.scala spark/src/main/scala/org/apache/spark/sql/delta/DeltaOperations.scala — FileTooLong — 796 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 296 over it, 1.59× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: uccommitcoordinator/UCDeltaTokenBasedRestClient.java storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java — FileTooLong — 788 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 288 over it, 1.58× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: commands/VacuumCommand.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/VacuumCommand.scala — FileTooLong — 757 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 257 over it, 1.51× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/DeltaLog.scala spark/src/main/scala/org/apache/spark/sql/delta/DeltaLog.scala — FileTooLong — 727 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 227 over it, 1.45× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: connect/tables.py python/delta/connect/tables.py — FileTooLong — 704 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 204 over it, 1.41× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: amt/AMTWriterManager.scala spark/src/main/scala/org/apache/spark/sql/delta/amt/AMTWriterManager.scala — FileTooLong — 701 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 201 over it, 1.40× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: internal/TransactionImpl.java kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java — FileTooLong — 694 significant lines (blank, comment-only and punctuation-only lines excluded), about 91% of them inside a single declaration: TransactionImpl (78-1116). The bar is 500 significant lines; this is 194 over it, 1.39× the bar. Moving the declarations that sit BESIDE it into sibling files will not shorten this file. Extract from INSIDE that declaration instead: lift each cohesive group of its body — the parts that share the same inputs and are named together — into its own unit in a sibling file, and have the original call them.
FileTooLong: delta/Checksum.scala spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala — FileTooLong — 686 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 186 over it, 1.37× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: delta/tables.py python/delta/tables.py — FileTooLong — 678 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 178 over it, 1.36× the bar. To reduce it, split the file along the responsibilities already in it: move each cohesive group of declarations into its own sibling file in the same module or package, so no one file has to be read whole to change one of them.
FileTooLong: hive/HiveCatalog.java icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java — FileTooLong — 666 significant lines (blank, comment-only and punctuation-only lines excluded), about 91% of them inside a single declaration: HiveCatalog (86-1011). The bar is 500 significant lines; this is 166 over it, 1.33× the bar. Moving the declarations that sit BESIDE it into sibling files will not shorten this file. Extract from INSIDE that declaration instead: lift each cohesive group of its body — the parts that share the same inputs and are named together — into its own unit in a sibling file, and have the original call them.
+ 17 more in this group — see findings.md.

D3 · God Classes · TooManyMethods · ×30

TooManyMethods: DeltaErrorsBase REDACTED:186 — TooManyMethods — 535 methods. The bar is 30 methods; this is 505 over it, 17.83× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: OptimisticTransactionImpl spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:310 — TooManyMethods — 115 methods. The bar is 30 methods; this is 85 over it, 3.83× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaErrors kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaErrors.java:43 — TooManyMethods — 77 methods. The bar is 30 methods; this is 47 over it, 2.57× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: TableMetadata icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:66 — TooManyMethods — 71 methods. The bar is 30 methods; this is 41 over it, 2.37× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: Builder icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:928 — TooManyMethods — 60 methods. The bar is 30 methods; this is 30 over it, 2.00× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: SchemaUtils spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala:67 — TooManyMethods — 53 methods. The bar is 30 methods; this is 23 over it, 1.77× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaV2MicroBatchStream spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:110 — TooManyMethods — 52 methods. The bar is 30 methods; this is 22 over it, 1.73× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: AbstractKernelTable flink/src/main/java/io/delta/flink/table/AbstractKernelTable.java:80 — TooManyMethods — 47 methods. The bar is 30 methods; this is 17 over it, 1.57× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaTable spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaTable.scala:41 — TooManyMethods — 44 methods. The bar is 30 methods; this is 14 over it, 1.47× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: HiveCatalog icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:86 — TooManyMethods — 43 methods. The bar is 30 methods; this is 13 over it, 1.43× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: Snapshot spark/src/main/scala/org/apache/spark/sql/delta/Snapshot.scala:116 — TooManyMethods — 43 methods. The bar is 30 methods; this is 13 over it, 1.43× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: TransactionImpl kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java:78 — TooManyMethods — 42 methods. The bar is 30 methods; this is 12 over it, 1.40× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: SnapshotManagement spark/src/main/scala/org/apache/spark/sql/delta/SnapshotManagement.scala:66 — TooManyMethods — 42 methods. The bar is 30 methods; this is 12 over it, 1.40× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: FlinkUnityCatalog flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalog.java:36 — TooManyMethods — 41 methods. The bar is 30 methods; this is 11 over it, 1.37× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaTable spark/src/main/scala/io/delta/tables/DeltaTable.scala:45 — TooManyMethods — 40 methods. The bar is 30 methods; this is 10 over it, 1.33× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: FileNames spark/src/main/scala/org/apache/spark/sql/delta/util/FileNames.scala:25 — TooManyMethods — 40 methods. The bar is 30 methods; this is 10 over it, 1.33× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaColumnMappingBase spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnMapping.scala:54 — TooManyMethods — 39 methods. The bar is 30 methods; this is 9 over it, 1.30× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: FileNames kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/FileNames.java:29 — TooManyMethods — 37 methods. The bar is 30 methods; this is 7 over it, 1.23× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaLog spark/src/main/scala/org/apache/spark/sql/delta/DeltaLog.scala:79 — TooManyMethods — 37 methods. The bar is 30 methods; this is 7 over it, 1.23× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaV2Scan spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2Scan.java:68 — TooManyMethods — 37 methods. The bar is 30 methods; this is 7 over it, 1.23× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaTable python/delta/tables.py:39 — TooManyMethods — 36 methods. The bar is 30 methods; this is 6 over it, 1.20× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: LogSegment kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/LogSegment.java:39 — TooManyMethods — 35 methods. The bar is 30 methods; this is 5 over it, 1.17× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: ConflictChecker spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:272 — TooManyMethods — 35 methods. The bar is 30 methods; this is 5 over it, 1.17× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: DeltaLog spark/src/main/scala/org/apache/spark/sql/delta/DeltaLog.scala:840 — TooManyMethods — 33 methods. The bar is 30 methods; this is 3 over it, 1.10× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
TooManyMethods: PartitionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:100 — TooManyMethods — 33 methods. The bar is 30 methods; this is 3 over it, 1.10× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
+ 5 more in this group — see findings.md.

D17 · Explicit Debt · HackComment · ×22

HackComment spark/src/test/scala/org/apache/spark/sql/delta/test/CustomCatalogs.scala:93 — // hack hack: no-op just for testing — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment spark/src/test/scala/org/apache/spark/sql/delta/test/CustomCatalogs.scala:183 — // hack hack: no-op just for testing — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment spark/src/test/scala/org/apache/spark/sql/delta/rowid/RowIdSuite.scala:839 — // Hack to enable row tracking without triggering a backfill. — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:952 — // HACK ALERT: since there is no DSV2 API for getting table path before creation, — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment spark/src/main/scala/org/apache/spark/sql/delta/perf/DeltaOptimizedWriterExec.scala:153 — // hack to materialize the shuffle files in a fault tolerant way — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/MetadataUpdate.java:115 — // HACK-HACK This is modified — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/MetadataUpdate.java:120 — // HACK-HACK This is modified — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:509 — // HACK-HACK This is modified — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:773 — // HACK-HACK This is modified — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:206 — // HACK-HACK This is modified — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/PartitionSpec.java:390 — // HACK-HACK: disable checkConflicts for partition spec converted from Delta — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:1047 — // Hack-Hack This is added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:110 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:115 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:87 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:89 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:154 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:178 — // HACK-HACK This is newly added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:523 — // HACK-HACK This is added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:243 — // HACK-HACK This is newely added — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:248 — // HACK-HACK This is newely added: use storage descriptor from Delta — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.
HackComment icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:251 — // HACK-HACK This is newely added: set schema to be empty to match Delta behavior — a workaround marked in source: record what it is compensating for and what would allow its removal (the upstream fix, the API it is waiting on, the invariant it restores), so the next reader can judge whether it is still needed rather than rediscovering why it is there.

D3 · God Classes · ClassTooLong · ×18

ClassTooLong: TableMetadata icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:66 — ClassTooLong — 1230 significant lines (blank, comment-only and punctuation-only lines excluded), 71 methods. The bar is 400 significant lines; this is 830 over it, 3.08× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: DeltaV2MicroBatchStream spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:110 — ClassTooLong — 1122 significant lines (blank, comment-only and punctuation-only lines excluded), 52 methods. The bar is 400 significant lines; this is 722 over it, 2.81× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: DeltaAnalysis spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:84 — ClassTooLong — 731 significant lines (blank, comment-only and punctuation-only lines excluded), 9 methods. The bar is 400 significant lines; this is 331 over it, 1.83× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: UCCommitCoordinatorClient storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:52 — ClassTooLong — 636 significant lines (blank, comment-only and punctuation-only lines excluded), 23 methods. The bar is 400 significant lines; this is 236 over it, 1.59× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: TransactionImpl kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java:78 — ClassTooLong — 635 significant lines (blank, comment-only and punctuation-only lines excluded), 42 methods. The bar is 400 significant lines; this is 235 over it, 1.59× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: HiveCatalog icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:86 — ClassTooLong — 609 significant lines (blank, comment-only and punctuation-only lines excluded), 43 methods. The bar is 400 significant lines; this is 209 over it, 1.52× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: DefaultExpressionEvaluator kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:43 — ClassTooLong — 563 significant lines (blank, comment-only and punctuation-only lines excluded), 4 methods. The bar is 400 significant lines; this is 163 over it, 1.41× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: PartitionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:100 — ClassTooLong — 540 significant lines (blank, comment-only and punctuation-only lines excluded), 33 methods. The bar is 400 significant lines; this is 140 over it, 1.35× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: BitPacking spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:28 — ClassTooLong — 540 significant lines (blank, comment-only and punctuation-only lines excluded), 29 methods. The bar is 400 significant lines; this is 140 over it, 1.35× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: TableFeatures kernel/kernel-api/src/main/java/io/delta/kernel/internal/tablefeatures/TableFeatures.java:39 — ClassTooLong — 478 significant lines (blank, comment-only and punctuation-only lines excluded), 22 methods. The bar is 400 significant lines; this is 78 over it, 1.20× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: ChecksumUtils kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java:53 — ClassTooLong — 469 significant lines (blank, comment-only and punctuation-only lines excluded), 21 methods. The bar is 400 significant lines; this is 69 over it, 1.17× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: DynamoDBCommitCoordinatorClient spark/src/main/java/io/delta/dynamodbcommitcoordinator/DynamoDBCommitCoordinatorClient.java:55 — ClassTooLong — 469 significant lines (blank, comment-only and punctuation-only lines excluded), 14 methods. The bar is 400 significant lines; this is 69 over it, 1.17× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: SchemaUtils kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:43 — ClassTooLong — 467 significant lines (blank, comment-only and punctuation-only lines excluded), 29 methods. The bar is 400 significant lines; this is 67 over it, 1.17× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: DeltaErrors kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaErrors.java:43 — ClassTooLong — 462 significant lines (blank, comment-only and punctuation-only lines excluded), 77 methods. The bar is 400 significant lines; this is 62 over it, 1.16× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: TransactionMetadataFactory kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionMetadataFactory.java:58 — ClassTooLong — 443 significant lines (blank, comment-only and punctuation-only lines excluded), 22 methods. The bar is 400 significant lines; this is 43 over it, 1.11× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: AbstractKernelTable flink/src/main/java/io/delta/flink/table/AbstractKernelTable.java:80 — ClassTooLong — 425 significant lines (blank, comment-only and punctuation-only lines excluded), 47 methods. The bar is 400 significant lines; this is 25 over it, 1.06× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: ExpressionUtils spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:54 — ClassTooLong — 424 significant lines (blank, comment-only and punctuation-only lines excluded), 14 methods. The bar is 400 significant lines; this is 24 over it, 1.06× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
ClassTooLong: SnapshotManager kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java:48 — ClassTooLong — 415 significant lines (blank, comment-only and punctuation-only lines excluded), 14 methods. The bar is 400 significant lines; this is 15 over it, 1.04× the bar. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.

D3 · God Classes · MethodTooLong · ×13

MethodTooLong: UCCommitCoordinatorClient.commitImpl storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:325 — MethodTooLong — commitImpl runs 247 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 147 over it, 2.47× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: SnapshotManager.buildLogSegmentFromStartCheckpointVersion kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java:313 — MethodTooLong — buildLogSegmentFromStartCheckpointVersion runs 186 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 86 over it, 1.86× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: ExpressionUtils.dsv2PredicateToCatalystExpression spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:572 — MethodTooLong — dsv2PredicateToCatalystExpression runs 183 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 83 over it, 1.83× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: ChecksumUtils.buildCrcInfoIncrementally kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java:376 — MethodTooLong — buildCrcInfoIncrementally runs 165 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 65 over it, 1.65× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: IntervalParser.toMicroSeconds kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/IntervalParserUtils.java:110 — MethodTooLong — toMicroSeconds runs 157 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 57 over it, 1.57× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: DefaultJsonRow.decodeElement kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultJsonRow.java:136 — MethodTooLong — decodeElement runs 155 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 55 over it, 1.55× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: HiveTableOperations.doCommit icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:176 — MethodTooLong — doCommit runs 141 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 41 over it, 1.41× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: JsonUtils.parseJsonValueToLiteral kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/JsonUtils.java:115 — MethodTooLong — parseJsonValueToLiteral runs 130 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 30 over it, 1.30× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: DynamoDBCommitCoordinatorClient.commitToCoordinator spark/src/main/java/io/delta/dynamodbcommitcoordinator/DynamoDBCommitCoordinatorClient.java:200 — MethodTooLong — commitToCoordinator runs 116 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 16 over it, 1.16× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: TableMetadata.<init> icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:290 — MethodTooLong — <init> runs 114 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 14 over it, 1.14× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1808 — MethodTooLong — collectAndBuildCDCIndexedFiles runs 113 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 13 over it, 1.13× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: ParquetFilterUtils.convertComparatorToParquetFilter kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:162 — MethodTooLong — convertComparatorToParquetFilter runs 110 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 10 over it, 1.10× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: ParquetFileWriter.write kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFileWriter.java:134 — MethodTooLong — write runs 106 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 6 over it, 1.06× the bar. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.

D4 · Code Duplication · Duplicated block (9 lines × 2) · ×13

Duplicated block (9 lines × 2) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:219 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:219-227 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:95-103 — before extracting anything, compare `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala` as WHOLE FILES: this scan already matched 4 separate duplicated blocks between them, totalling at least 39 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. The two sit in different directories, so one cannot simply be deleted in favour of the other while both are reached separately: hoist the shared part into a location both already depend on and have each file call it, and retire whichever file turns out to have no caller of its own left. Extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:219` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaOptimizeBuilder.scala:87 — spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaOptimizeBuilder.scala:87-95 | spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaTable.scala:848-856 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaOptimizeBuilder.scala:87` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/DeltaFileProviderUtils.scala:79 — spark/src/main/scala/org/apache/spark/sql/delta/DeltaFileProviderUtils.scala:79-87 | spark/src/main/scala/org/apache/spark/sql/delta/SnapshotManagement.scala:1846-1854 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/DeltaFileProviderUtils.scala:79` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.
Duplicated block (9 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/MergeOutputGeneration.scala:274 — spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/MergeOutputGeneration.scala:274-282 | spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/MergeOutputGeneration.scala:284-292 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (9 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:348 — spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:348-356 | spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:365-373 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:348` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.
Duplicated block (9 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:61 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:61-69 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala:61-69 — before extracting anything, compare `spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 34 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place.
Duplicated block (9 lines × 2) flink/src/main/java/io/delta/flink/kernel/ColumnVectorUtils.java:59 — flink/src/main/java/io/delta/flink/kernel/ColumnVectorUtils.java:59-67 | flink/src/main/java/io/delta/flink/sink/Conversions.java:267-275 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `flink/src/main/java/io/delta/flink/kernel/ColumnVectorUtils.java:59` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (9 lines × 2) icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:386 — icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:386-394 | icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:405-416 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:386` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:296 — icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:296-306 | icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:339-347 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:296` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:288 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:288-296 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:346-354 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:288` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:345` calls `writeByte` and `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:287` does not — after which the two agree again for 4 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (9 lines × 2) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:305 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:305-313 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:363-371 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:305` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.
Duplicated block (9 lines × 2) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:608 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:608-616 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:634-642 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:608` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (9 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:84 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:84-92 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/SingleThreadedTableReader.java:62-70 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.

X3 · Exception handling · Swallowed exception (caught, then discarded) · ×13

Swallowed exception (caught, then discarded) spark/src/main/scala-shims/spark-4.1-4.3/VariantShreddingShims.scala:59 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:131 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:169 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/DeltaLog.scala:663 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/DeltaUnsupportedOperationsCheck.scala:45 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala:370 — `case _` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/TableFeature.scala:436 — `case _` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/stats/DeltaScan.scala:109 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:92 — `case e: Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/IcebergRESTCatalogPlanningClient.scala:265 — `case _: Exception` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:273 — `case NonFatal(_)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) flink/src/main/java/io/delta/flink/table/AbstractKernelTable.java:466 — `catch (Exception)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.
Swallowed exception (caught, then discarded) flink/src/main/java/io/delta/flink/table/CatalogManagedTable.java:175 — `catch (Exception)` takes every exception and records none of it — the body neither logs it, rethrows it, nor even names it, so the failure is discarded as completely as by an empty catch and only the substituted value survives. Log it through whatever this codebase already uses to report problems, narrow the catch to the exception this call can actually raise, or say in a comment on the catch why the failure genuinely cannot matter.

D4 · Code Duplication · Duplicated block (7 lines × 2) · ×11

Duplicated block (7 lines × 2) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:188 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:188-194 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:64-70 — before extracting anything, compare `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala` as WHOLE FILES: this scan already matched 4 separate duplicated blocks between them, totalling at least 39 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. The two sit in different directories, so one cannot simply be deleted in favour of the other while both are reached separately: hoist the shared part into a location both already depend on and have each file call it, and retire whichever file turns out to have no caller of its own left. Extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:188` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.
Duplicated block (7 lines × 2) spark/src/main/scala/io/delta/tables/DeltaMergeBuilder.scala:481 — spark/src/main/scala/io/delta/tables/DeltaMergeBuilder.scala:481-487 | spark/src/main/scala/io/delta/tables/DeltaMergeBuilder.scala:683-689 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/io/delta/tables/DeltaMergeBuilder.scala:481` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:488 — spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:488-494 | spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:496-502 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:488` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:130 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:130-136 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:235-241 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (7 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:140 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:140-146 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/CRCInfo.java:244-250 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (7 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/PartitionUtils.java:322 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/PartitionUtils.java:322-328 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/PartitionUtils.java:373-379 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/PartitionUtils.java:322` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:469 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:469-475 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:497-503 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:469` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/cdc/CDCReadFunction.java:125 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/cdc/CDCReadFunction.java:125-131 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/deletionvector/DeletionVectorReadFunction.java:99-105 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/cdc/CDCReadFunction.java:125` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:390 — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:390-396 | storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCTokenBasedRestClient.java:370-376 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.
Duplicated block (7 lines × 2) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:598 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:598-604 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:624-630 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:598` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 2) python/delta/connect/tables.py:855 — python/delta/connect/tables.py:855-861 | python/delta/tables.py:1681-1687 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice.

D15 · Churn × Complexity Hotspots · Hotspot · ×10

Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2582 — spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala changed 36 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 21 in OptimisticTransactionImpl.prepareInitialActions at line 2582. 4 of those changes were fix/bug commits, and the other 32 changed it for other reasons — this file is under both repair and feature pressure. Before the next change lands here, make sure the area it touches is under test, then split that area out of the file so the following change is smaller than this one — a file this often edited pays the complexity back every time. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:90 — spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala changed 3 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 115 in DeltaAnalysis.apply at line 90. 1 of those changes was a fix/bug commit, and the other 2 changed it for other reasons — this file is under both repair and feature pressure. Before the next change lands here, make sure the area it touches is under test, then split that area out of the file so the following change is smaller than this one — a file this often edited pays the complexity back every time. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:1599 — spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala changed 10 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 22 in ConflictChecker.trackDataChange at line 1599. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala:136 — spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala changed 3 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 61 in WriteIntoDelta.writeAndReturnCommitData at line 136. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala:353 — spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala changed 6 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 23 in RecordChecksum.computeNewChecksum at line 353. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:230 — spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala changed 5 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 25 in CDCReaderImpl.changesToDF at line 230. 1 of those changes was a fix/bug commit, and the other 4 changed it for other reasons — this file is under both repair and feature pressure. Before the next change lands here, make sure the area it touches is under test, then split that area out of the file so the following change is smaller than this one — a file this often edited pays the complexity back every time. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java:602 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java changed 5 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 23 in MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges at line 602. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: spark/src/main/scala/org/apache/spark/sql/delta/actions/InMemoryLogReplay.scala spark/src/main/scala/org/apache/spark/sql/delta/actions/InMemoryLogReplay.scala:74 — spark/src/main/scala/org/apache/spark/sql/delta/actions/InMemoryLogReplay.scala changed 5 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 18 in InMemoryLogReplay.append at line 74. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- spark/src/main/scala/org/apache/spark/sql/delta/actions/InMemoryLogReplay.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala:343 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala changed 5 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 15 in IcebergConverter.convertSnapshotInternal at line 343. Frequent change and high complexity in one file compound: schedule the next change to it to include carving out the part being edited, with the area under test before it moves. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.
Hotspot: flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java:129 — flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java changed 3 times in last 90 days, and the most complex body those changes touched has cyclomatic complexity 22 in FlinkUnityCatalogTable.fromJson at line 129. 1 of those changes was a fix/bug commit, and the other 2 changed it for other reasons — this file is under both repair and feature pressure. Before the next change lands here, make sure the area it touches is under test, then split that area out of the file so the following change is smaller than this one — a file this often edited pays the complexity back every time. Counted over 2026-07-27..2026-10-25, the 90 days ending at the analysed commit. Reproduce with `git log --since='2026-07-27 20:59:54 -07:00' --until='2026-10-25 20:59:54 -07:00' --full-history --no-merges -- flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java`: merges are excluded because a merge re-states changes already counted at their own commits, and history is NOT path-simplified because a change that reached the file through a merged branch is still a change to it. That command counts raw commits and can read HIGHER than this row, which counts a cherry-picked re-land, and a revert together with the commit it undoes, once each — a difference of several commits on a file whose history was re-landed or reverted inside the window.

D36 · Supply-chain Provenance & Signing · REDACTED

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D4 · Code Duplication · Duplicated block (6 lines × 2) · ×9

Duplicated block (6 lines × 2) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:181 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:181-186 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:57-62 — before extracting anything, compare `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala` as WHOLE FILES: this scan already matched 4 separate duplicated blocks between them, totalling at least 39 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. The two sit in different directories, so one cannot simply be deleted in favour of the other while both are reached separately: hoist the shared part into a location both already depend on and have each file call it, and retire whichever file turns out to have no caller of its own left. Extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:181` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:180 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:180-185 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:206-211 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:180` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:279 — spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:279-284 | spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:350-355 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:279` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:309 — spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:309-314 | spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:384-389 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/optimizablePartitionExpressions.scala:309` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaLogActionUtils.java:326 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaLogActionUtils.java:326-332 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java:149-154 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaLogActionUtils.java:326` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:304 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:304-309 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:317-322 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:304` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (6 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2Write.java:123 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2Write.java:123-128 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/write/DeltaV2WriteBuilder.java:82-87 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.
Duplicated block (6 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/BaseTableWriter.java:78 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/BaseTableWriter.java:78-83 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/BaseTableWriter.java:122-127 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (6 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTable.java:43 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTable.java:43-48 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:52-59 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.

D4 · Code Duplication · Duplicated block (10 lines × 2) · ×8

Duplicated block (10 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:90 — spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:90-99 | spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:197-206 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:90` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:87` calls `canUpCast` and `spark/src/main/scala/org/apache/spark/sql/delta/TypeWidening.scala:194` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (10 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:359 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:359-368 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:387-396 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:359` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/RowId.scala:72 — spark/src/main/scala/org/apache/spark/sql/delta/RowId.scala:72-81 | spark/src/main/scala/org/apache/spark/sql/delta/RowTracking.scala:44-53 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.
Duplicated block (10 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/CreateTableTransactionBuilderImpl.java:126 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/CreateTableTransactionBuilderImpl.java:126-135 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/ReplaceTableTransactionBuilderV2Impl.java:110-120 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `kernel/kernel-api/src/main/java/io/delta/kernel/internal/CreateTableTransactionBuilderImpl.java:122` calls `resolvePath`, `throwIfTableAlreadyExists` and `kernel/kernel-api/src/main/java/io/delta/kernel/internal/ReplaceTableTransactionBuilderV2Impl.java:108` does not — after which the two agree again for 3 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (10 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/stats/FileSizeHistogram.java:325 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/stats/FileSizeHistogram.java:325-334 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/stats/FileSizeHistogram.java:353-362 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/stats/FileSizeHistogram.java:325` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultRowBasedColumnarBatch.java:102 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultRowBasedColumnarBatch.java:102-111 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultRowBasedColumnarBatch.java:138-147 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultRowBasedColumnarBatch.java:102` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (10 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:283 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:283-292 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:341-350 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:283` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:368 — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:368-377 | storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCTokenBasedRestClient.java:343-353 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (5 lines × 2) · ×7

Duplicated block (5 lines × 2) REDACTED:149 — REDACTED:149-153 | REDACTED:137-141 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.
Duplicated block (5 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionBuilderImpl.java:329 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionBuilderImpl.java:329-333 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/UpdateTableTransactionBuilderImpl.java:141-145 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionBuilderImpl.java:329` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:478 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:478-482 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:506-510 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionEvaluator.java:478` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1284 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1284-1288 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java:301-305 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1284` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java:210 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java:210-214 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java:349-354 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (5 lines × 2) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:767 — storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:767-771 | storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCTokenBasedRestClient.java:262-266 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:767` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:199 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:199-203 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/RemoveFile.java:129-133 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D35 · Change Coupling · Change coupling · ×6

Change coupling: TransactionBuilder.java ↔ TransactionImpl.java kernel/kernel-api/src/main/java/io/delta/kernel/TransactionBuilder.java:1 — `kernel/kernel-api/src/main/java/io/delta/kernel/TransactionBuilder.java` and `kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java` change together 70% of the time (7 of the 10 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets) with no explicit dependency — the edge is real but nothing declares it. Read the pair before acting: if one registers itself into the other through a hook or an initialiser, the missing dependency is DELIBERATE — the registration is the link, and it is meant not to be an import — and the thing to add is a comment on each side naming the other, not a merge; if they simply belong together, co-locate them; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 7 shared commits counted here, the most recent 3 are `9d3a8e72` Add support for writing log compaction files (#4334); `b5b5f6f9` [Kernel][Clustering #4] add withClusteringColumn api (#4327); `eb593f8e` Allow DomainMetadata to be set in Transaction instead of TransactionB… — run `git show` on any of them.
Change coupling: DefaultExpressionUtils.java ↔ ExpressionVisitor.java kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:1 — `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java` and `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/ExpressionVisitor.java` change together 69% of the time (9 of the 13 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets). They sit in the same directory, and in this ecosystem sibling files there normally share one namespace/package — so a direct reference between them needs no import and this pass cannot see whether one exists. Read the pair before acting: if one file only DECLARES what the other consumes (a constants/types file beside its user), the co-change is definitional and the question is whether the split earns its keep; if they duplicate structure, extract the common part into a shared function or type they both call; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 9 shared commits counted here, the most recent 3 are `9c389562` [KERNEL] Partition pruning with collations (#5354); `5280b4fb` [Kernel]In expression support in kernel (#5186); `eb318861` [KERNEL] Extend Predicate to include `collationIdentifier` (#4250) — run `git show` on any of them.
Change coupling: ClassicMergeExecutor.scala ↔ InsertOnlyMergeExecutor.scala spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/ClassicMergeExecutor.scala:1 — `spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/ClassicMergeExecutor.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/InsertOnlyMergeExecutor.scala` change together 67% of the time (8 of the 12 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets). They sit in the same directory, and in this ecosystem sibling files there normally share one namespace/package — so a direct reference between them needs no import and this pass cannot see whether one exists. Read the pair before acting: if one file only DECLARES what the other consumes (a constants/types file beside its user), the co-change is definitional and the question is whether the split earns its keep; if they duplicate structure, extract the common part into a shared function or type they both call; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 8 shared commits counted here, the most recent 3 are `64c9b979` Revert "[Spark] Add custom not matched for insert clauses expr (#3405…; `1d9ad36f` [Spark] Add custom not matched for insert clauses expr (#3405); `679e4441` Disentangle schema evolution in MERGE INTO command (#2709) — run `git show` on any of them.
Change coupling: SnapshotManagement.scala ↔ CheckpointHook.scala spark/src/main/scala/org/apache/spark/sql/delta/SnapshotManagement.scala:1 — `spark/src/main/scala/org/apache/spark/sql/delta/SnapshotManagement.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/hooks/CheckpointHook.scala` change together 56% of the time (9 of the 16 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets) with no explicit dependency — the edge is real but nothing declares it. Read the pair before acting: if one registers itself into the other through a hook or an initialiser, the missing dependency is DELIBERATE — the registration is the link, and it is meant not to be an import — and the thing to add is a comment on each side naming the other, not a merge; if they simply belong together, co-locate them; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 9 shared commits counted here, the most recent 3 are `b22496ee` Add inline manifest-tree checkpoint support for adaptive metadata tab…; `cda8a349` [SPARK] Block Time Travel beyond DeletedFileRetentionDuration (#5022); `fcc3d9bc` [Spark] Pass catalog table to DeltaLog API call sites (#3862) — run `git show` on any of them.
Change coupling: Table.java ↔ SnapshotManager.java kernel/kernel-api/src/main/java/io/delta/kernel/Table.java:1 — `kernel/kernel-api/src/main/java/io/delta/kernel/Table.java` and `kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java` change together 50% of the time (6 of the 12 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets) with no explicit dependency — the edge is real but nothing declares it. Read the pair before acting: if one registers itself into the other through a hook or an initialiser, the missing dependency is DELIBERATE — the registration is the link, and it is meant not to be an import — and the thing to add is a comment on each side naming the other, not a merge; if they simply belong together, co-locate them; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 6 shared commits counted here, the most recent 3 are `c426f030` [Kernel] Refactor all user-facing exceptions to be "KernelExceptions"…; `5f2d957a` [Kernel][Writes] Implement `Table.checkpoint` API to write a classic …; `f50bd83e` [Kernel] Support getting snapshots by timestamp (time-travel) (#2662) — run `git show` on any of them.
Change coupling: DefaultJsonHandler.java ↔ DefaultParquetHandler.java kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/engine/DefaultJsonHandler.java:1 — `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/engine/DefaultJsonHandler.java` and `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/engine/DefaultParquetHandler.java` change together 50% of the time (5 of the 10 commits that touched whichever of the two files changed less often, counting a file under its earlier names as well — a repo-wide or module-wide sweep is evidence about the sweep rather than about any pair inside it and is left out of BOTH sides of this ratio, while a dependency bump, a formatter/rename sweep, or a commit whose edit to one of the two files was a tool directive such as //go:generate or whitespace only is left out of the shared count ONLY, so the two sides are not taken over identical commit sets). They sit in the same directory, and in this ecosystem sibling files there normally share one namespace/package — so a direct reference between them needs no import and this pass cannot see whether one exists. Read the pair before acting: if one file only DECLARES what the other consumes (a constants/types file beside its user), the co-change is definitional and the question is whether the split earns its keep; if they duplicate structure, extract the common part into a shared function or type they both call; if neither holds, the coupling is hidden and worth breaking. You can check this without leaving the row: of the 5 shared commits counted here, the most recent 3 are `51e1f38b` [Kernel][Defaults] Add `fileSize` as argument to `FileIO.newInputFile…; `05e647ab` [Kernel] Fix issue querying tables with spaces in the name (#3291); `7f199feb` [Kernel][Writes] Add support of inserting data into tables (#3030) — run `git show` on any of them.

D4 · Code Duplication · Duplicated block (12 lines × 2) · ×6

Duplicated block (12 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:96 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:96-107 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala:101-112 — before extracting anything, compare `spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 34 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:96` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:312 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:312-323 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:338-349 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:312` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:197 — spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:197-208 | spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:217-228 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:197` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:706 — icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:706-717 | icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:732-743 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:706` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:558 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:558-570 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:572-583 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:572` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 2) examples/scala/src/main/scala/example/IcebergCompatV2.scala:75 — examples/scala/src/main/scala/example/IcebergCompatV2.scala:75-86 | examples/scala/src/main/scala/example/UniForm.scala:98-109 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `examples/scala/src/main/scala/example/IcebergCompatV2.scala:75` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (11 lines × 2) · ×6

Duplicated block (11 lines × 2) spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaMergeBuilder.scala:472 — spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaMergeBuilder.scala:472-482 | spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaMergeBuilder.scala:681-691 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaMergeBuilder.scala:472` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (11 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/commands/alterDeltaTableCommands.scala:422 — spark/src/main/scala/org/apache/spark/sql/delta/commands/alterDeltaTableCommands.scala:422-432 | spark/src/main/scala/org/apache/spark/sql/delta/commands/alterDeltaTableCommands.scala:535-545 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (11 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:47 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:47-57 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:87-97 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (11 lines × 2) storage/src/main/java/io/delta/storage/HDFSLogStore.java:132 — storage/src/main/java/io/delta/storage/HDFSLogStore.java:132-142 | storage/src/main/java/io/delta/storage/HadoopFileSystemLogStore.java:121-131 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `storage/src/main/java/io/delta/storage/HDFSLogStore.java:132` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (11 lines × 2) flink/src/main/java/io/delta/flink/sink/mergestrategy/AppendOnly.java:116 — flink/src/main/java/io/delta/flink/sink/mergestrategy/AppendOnly.java:116-127 | flink/src/main/java/io/delta/flink/sink/mergestrategy/Upsert.java:184-194 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `flink/src/main/java/io/delta/flink/sink/mergestrategy/AppendOnly.java:116` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.
Duplicated block (11 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:141 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:141-151 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:153-163 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:141` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.

X3 · Exception handling · Swallowed exception (empty catch) · ×5

Swallowed exception (empty catch) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:1417 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.
Swallowed exception (empty catch) spark/src/main/scala/org/apache/spark/sql/delta/RowIndexFilterMetadataColumnUtils.scala:181 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.
Swallowed exception (empty catch) spark/src/main/scala/io/delta/sql/AbstractDeltaSparkSessionExtension.scala:149 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.
Swallowed exception (empty catch) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/Utils.java:131 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.
Swallowed exception (empty catch) flink/src/main/java/io/delta/flink/kernel/CheckpointWriter.java:169 — An empty catch block silently discards the error — failures vanish with no log and no rethrow. Log it, handle it, or don't catch it.

D4 · Code Duplication · Duplicated block (16 lines × 2) · ×4

Duplicated block (16 lines × 2) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:684 — sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:684-699 | sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:820-835 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (16 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:224 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:224-239 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:293-308 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:224` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (16 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:741 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:741-756 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:760-775 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:741` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (16 lines × 2) examples/scala/src/main/scala/example/IcebergCompatV2.scala:45 — examples/scala/src/main/scala/example/IcebergCompatV2.scala:45-60 | examples/scala/src/main/scala/example/UniForm.scala:46-61 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `examples/scala/src/main/scala/example/IcebergCompatV2.scala:45` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (8 lines × 2) · ×4

Duplicated block (8 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:382 — spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:382-389 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:406-413 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:382` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (8 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/DeltaConfig.scala:318 — spark/src/main/scala/org/apache/spark/sql/delta/DeltaConfig.scala:318-325 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaConfig.scala:333-340 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/DeltaConfig.scala:318` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (8 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:231 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:231-238 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/RemoveFile.java:92-99 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.
Duplicated block (8 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:254 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/AddFile.java:254-261 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/RemoveFile.java:115-122 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once.

D4 · Code Duplication · Duplicated block (13 lines × 2) · ×4

Duplicated block (13 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:46 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala:46-58 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala:46-58 — before extracting anything, compare `spark/src/main/scala/org/apache/spark/sql/delta/expressions/DecodeNestedZ85EncodedVariant.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/expressions/EncodeNestedVariantAsZ85String.scala` as WHOLE FILES: this scan already matched 3 separate duplicated blocks between them, totalling at least 34 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. If that is what happened, the fix is to keep one copy and have the other call it (or delete it), which resolves this row and its siblings together — extracting one helper per block leaves the fork in place.
Duplicated block (13 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:91 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:91-103 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:172-184 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/GenerateIcebergCompatActionUtils.java:91` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (13 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/Checkpointer.java:372 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/Checkpointer.java:372-384 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/Checkpointer.java:434-446 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/Checkpointer.java:372` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (13 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/expressions/And.java:39 — kernel/kernel-api/src/main/java/io/delta/kernel/expressions/And.java:39-51 | kernel/kernel-api/src/main/java/io/delta/kernel/expressions/Or.java:39-51 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D31 · IaC & Container Security · Medium IaC · ×3

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D4 · Code Duplication · Duplicated block (14 lines × 2) · ×3

Duplicated block (14 lines × 2) hudi/src/main/scala/org/apache/spark/sql/delta/hudi/HudiConversionTransaction.scala:353 — hudi/src/main/scala/org/apache/spark/sql/delta/hudi/HudiConversionTransaction.scala:353-366 | iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConversionTransaction.scala:688-701 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `hudi/src/main/scala/org/apache/spark/sql/delta/hudi/HudiConversionTransaction.scala:353` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (14 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/TableImpl.java:285 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/TableImpl.java:285-298 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/table/SnapshotFactory.java:170-183 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/TableImpl.java:285` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (14 lines × 2) docs/generate_docs.py:100 — docs/generate_docs.py:100-113 | kernel/examples/run-kernel-examples.py:128-141 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (9 lines × 3) · ×3

Duplicated block (9 lines × 3) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:405 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:405-413 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:465-473 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:526-534 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:405` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:462` calls `writeByte` and `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:402` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (9 lines × 3) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:422 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:422-430 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:482-490 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:543-551 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:422` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.
Duplicated block (9 lines × 3) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java:105 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java:105-113 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java:128-137 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/StreamingHelper.java:335-343 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.

D4 · Code Duplication · Duplicated block (8 lines × 7) · ×3

Duplicated block (8 lines × 7) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:171 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:171-178 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:223-230 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:279-286 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:336-343 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:394-401 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:453-460 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:513-520 — all 7 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:171` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:288` calls `writeByte` and `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:232` does not — after which the two agree again for 3 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (8 lines × 7) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:188 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:188-195 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:241-248 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:298-305 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:356-363 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:415-422 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:475-482 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:536-543 — all 7 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:188` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (8 lines × 7) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:607 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:607-614 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:619-626 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:665-672 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:690-697 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:702-709 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:714-721 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:726-733 — all 7 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:607` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

X15 · Unvalidated length from an untrusted reader · Length read from the parsed input is spent without ever being bounded · ×3

Length read from the parsed input is spent without ever being bounded spark/src/main/scala/org/apache/spark/sql/delta/deletionvectors/RoaringBitmapArray.scala:585 — `numberOfBitmaps` is read from the bytes being parsed at line 580 (`getInt`), then used to size an `Array.fill` at line 585 — and nowhere in its scope is `numberOfBitmaps` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `numberOfBitmaps` against the bytes actually remaining and a maximum the format allows before allocating.
Length read from the parsed input is spent without ever being bounded kernel/kernel-api/src/main/java/io/delta/kernel/internal/deletionvectors/RoaringBitmapArray.java:164 — `numberOfBitmaps` is read from the bytes being parsed at line 159 (`getInt`), then used to size a `new RoaringBitmap[]` at line 164 — and nowhere in its scope is `numberOfBitmaps` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `numberOfBitmaps` against the bytes actually remaining and a maximum the format allows before allocating.
Length read from the parsed input is spent without ever being bounded flink/src/main/java/io/delta/flink/kernel/dv/BinDVAccess.java:139 — `length` is read from the bytes being parsed at line 118 (`readInt`), then used to size a `new byte[]` at line 139 — and nowhere in its scope is `length` bounded from above — compared to a limit, clamped, or checked against the input that remains (a zero or sign test, or the loop that counts up to it, bounds nothing). Whoever wrote those bytes therefore chooses the allocation directly: a 32-bit length asks for up to 2 GiB before a single byte of the payload is known to exist, which either exhausts the heap with an `OutOfMemoryError` or, negative, throws `NegativeArraySizeException` out of a parser whose failure path was written for malformed input, not for hostile input. Bound `length` against the bytes actually remaining and a maximum the format allows before allocating.

D17 · Explicit Debt · FixmeComment · ×2

FixmeComment spark/src/test/scala/org/apache/spark/sql/delta/DeltaInsertIntoTableSuite.scala:1572 — // FIXME: Documenting existing behaviour. Fixing this should be a bugfix and not behavior change. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
FixmeComment spark/src/main/scala/org/apache/spark/sql/delta/commands/DeltaCommandInvariants.scala:82 — // FIXME: Needs inline type annotations because otherwise compiler gets confused on — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.

D4 · Code Duplication · Duplicated block (21 lines × 2) · ×2

Duplicated block (21 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:518 — spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:518-538 | spark/src/main/scala/org/apache/spark/sql/delta/commands/UpdateCommand.scala:421-441 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:518` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (21 lines × 2) storage-s3-dynamodb/src/main/java/io/delta/storage/BaseExternalLogStore.java:459 — storage-s3-dynamodb/src/main/java/io/delta/storage/BaseExternalLogStore.java:459-479 | storage/src/main/java/io/delta/storage/S3SingleDriverLogStore.java:89-109 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Each matched range is the entire body of the declaration above it, so the region is already a complete unit: move that whole declaration to the shared location and have each site call it, rather than lifting the lines out of their bodies. Any `return` inside it is the body's own exit and keeps its meaning in the moved unit.

D4 · Code Duplication · Duplicated block (17 lines × 2) · ×2

Duplicated block (17 lines × 2) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:195 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:195-211 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:71-87 — before extracting anything, compare `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala` and `spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala` as WHOLE FILES: this scan already matched 4 separate duplicated blocks between them, totalling at least 39 lines, which is the signature of one file having been copied from the other rather than of a helper waiting to be extracted. The two sit in different directories, so one cannot simply be deleted in favour of the other while both are reached separately: hoist the shared part into a location both already depend on and have each file call it, and retire whichever file turns out to have no caller of its own left. Extracting one helper per block leaves the fork in place. Read the line range as the matched WINDOW rather than a finished unit: at `iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:195` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.
Duplicated block (17 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:729 — spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:729-745 | spark/src/main/scala/org/apache/spark/sql/delta/commands/UpdateCommand.scala:483-499 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:729` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.

D4 · Code Duplication · Duplicated block (9–10 lines × 2) · ×2

Duplicated block (9–10 lines × 2) spark/src/main/scala/org/apache/spark/sql/delta/files/CdcAddFileIndex.scala:59 — spark/src/main/scala/org/apache/spark/sql/delta/files/CdcAddFileIndex.scala:59-67 | spark/src/main/scala/org/apache/spark/sql/delta/files/TahoeChangeFileIndex.scala:50-59 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/files/CdcAddFileIndex.scala:59` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (9–10 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/icebergcompat/IcebergUniversalFormatMetadataValidatorAndUpdater.java:63 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/icebergcompat/IcebergUniversalFormatMetadataValidatorAndUpdater.java:63-72 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/icebergcompat/IcebergUniversalFormatMetadataValidatorAndUpdater.java:75-83 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/icebergcompat/IcebergUniversalFormatMetadataValidatorAndUpdater.java:63` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (19–21 lines × 2) · ×2

Duplicated block (19–21 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaErrors.java:643 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaErrors.java:643-663 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaErrors.java:672-690 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Each matched range is the entire body of the declaration above it, so the region is already a complete unit: move that whole declaration to the shared location and have each site call it, rather than lifting the lines out of their bodies. Any `return` inside it is the body's own exit and keeps its meaning in the moved unit. Note first that the copies are not typed on the same thing: the declarations holding them bind `f` to `Supplier<T>` in one and `SupplierWithIOException<T>` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.
Duplicated block (19–21 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:186 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:186-206 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:228-246 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:186` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (18 lines × 2) · ×2

Duplicated block (18 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:155 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:155-172 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:186-203 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:155` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (18 lines × 2) docs/apis/generate_api_docs.py:157 — docs/apis/generate_api_docs.py:157-174 | docs/generate_docs.py:91-108 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (14–15 lines × 2) · ×2

Duplicated block (14–15 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:155 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:155-169 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:491-504 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (14–15 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:241 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:241-255 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:480-493 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:241` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.

D4 · Code Duplication · Duplicated block (11–12 lines × 2) · ×2

Duplicated block (11–12 lines × 2) REDACTED:127 — REDACTED:127-138 | REDACTED:119-129 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `REDACTED:127` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note first that the copies are not typed on the same thing: the declarations holding them bind `obj` to `DeltaCommittable` in one and `DeltaWriterResult` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `REDACTED:124` calls `writeUTF`, `getJobId`, `getOperatorId` and `REDACTED:118` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.
Duplicated block (11–12 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:221 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:221-231 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:856-867 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.

D4 · Code Duplication · Duplicated block (9 lines × 4) · ×2

Duplicated block (9 lines × 4) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:204 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:204-212 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:260-268 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:317-325 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:375-383 — all 4 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Each matched range is the entire body of the declaration above it, so the region is already a complete unit: move that whole declaration to the shared location and have each site call it, rather than lifting the lines out of their bodies. Any `return` inside it is the body's own exit and keeps its meaning in the moved unit.
Duplicated block (9 lines × 4) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:660 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:660-668 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:686-694 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:712-720 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:738-746 — all 4 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:660` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (7 lines × 3) · ×2

Duplicated block (7 lines × 3) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:581 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:581-587 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:607-613 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:633-639 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:581` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (7 lines × 3) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:738 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:738-747 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:760-766 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:779-785 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:738` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D6 · Cohesion (LCOM4) · Low cohesion · ×2

Low cohesion: IcebergRESTCatalogPlanningClient (LCOM4 4) iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/IcebergRESTCatalogPlanningClient.scala:72 — IcebergRESTCatalogPlanningClient's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.
Low cohesion: FileStatsHistogramAggBase (LCOM4 4) spark/src/main/scala/org/apache/spark/sql/delta/stats/FileStatsHistogram.scala:120 — FileStatsHistogramAggBase's methods fall into 4 groups that share no field and call none of each other, against a bar of more than 3 for this run (LCOM4, configurable — your repository's bar is the one quoted here). Each group is a set of methods reachable from one another through shared fields or direct calls, so 4 groups means the type has that many internally-connected clusters with nothing tying them together. Types whose shape makes a high count expected — and which would otherwise dominate this list — are excluded before this row is raised, so this is a genuine split candidate rather than a metric reading. It is still a shape, not a defect: confirm the groups match responsibilities you can name before splitting.

IC1 · Incompleteness & stubs · Empty method body · ×2

Empty method body — does nothing with its inputs spark/src/main/scala-shims/spark-4.0-4.1/DataSourceUtilsShims.scala:22 — `mergeWriteOptionsIntoHadoopConf` takes parameters but its body is empty — it accepts inputs and does nothing. Either implement it or remove it.
Empty method body — does nothing with its inputs spark/src/main/scala-shims/spark-4.0/VariantShreddingShims.scala:34 — `extractAndInjectVariantStats` takes parameters but its body is empty — it accepts inputs and does nothing. Either implement it or remove it.

D1 · Cyclomatic Complexity · DeltaAnalysis.apply (cyclomatic 115) · ×1

DeltaAnalysis.apply (cyclomatic 115) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:90 — DeltaAnalysis.apply has cyclomatic complexity 115 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67) · ×1

ExpressionUtils.dsv2PredicateToCatalystExpression (cyclomatic 67) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:572 — ExpressionUtils.dsv2PredicateToCatalystExpression has cyclomatic complexity 67 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · WriteIntoDelta.writeAndReturnCommitData (cyclomatic 61) · ×1

WriteIntoDelta.writeAndReturnCommitData (cyclomatic 61) spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala:136 — WriteIntoDelta.writeAndReturnCommitData has cyclomatic complexity 61 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · IntervalParser.toMicroSeconds (cyclomatic 60) · ×1

IntervalParser.toMicroSeconds (cyclomatic 60) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/IntervalParserUtils.java:110 — IntervalParser.toMicroSeconds has cyclomatic complexity 60 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · VariantStatsData.forPrefixAndStatType (cyclomatic 52) · ×1

VariantStatsData.forPrefixAndStatType (cyclomatic 52) spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:169 — VariantStatsData.forPrefixAndStatType has cyclomatic complexity 52 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DataFiltersBuilder.constructDataFilters (cyclomatic 51) · ×1

DataFiltersBuilder.constructDataFilters (cyclomatic 51) spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:241 — DataFiltersBuilder.constructDataFilters has cyclomatic complexity 51 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · DefaultJsonRow.decodeElement (cyclomatic 48) · ×1

DefaultJsonRow.decodeElement (cyclomatic 48) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultJsonRow.java:136 — DefaultJsonRow.decodeElement has cyclomatic complexity 48 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · JsonUtils.parseJsonValueToLiteral (cyclomatic 46) · ×1

JsonUtils.parseJsonValueToLiteral (cyclomatic 46) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/JsonUtils.java:115 — JsonUtils.parseJsonValueToLiteral has cyclomatic complexity 46 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · AbstractDeltaCatalog.alterTable (cyclomatic 40) · ×1

AbstractDeltaCatalog.alterTable (cyclomatic 40) spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:1175 — AbstractDeltaCatalog.alterTable has cyclomatic complexity 40 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · ParquetFilterUtils.convertComparatorToParquetFilter (cyclomatic 40) · ×1

ParquetFilterUtils.convertComparatorToParquetFilter (cyclomatic 40) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:162 — ParquetFilterUtils.convertComparatorToParquetFilter has cyclomatic complexity 40 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · DataSkippingUtils.constructDataSkippingFilter (cyclomatic 32) · ×1

DataSkippingUtils.constructDataSkippingFilter (cyclomatic 32) kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:157 — DataSkippingUtils.constructDataSkippingFilter has cyclomatic complexity 32 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · HiveTableOperations.doCommit (cyclomatic 32) · ×1

HiveTableOperations.doCommit (cyclomatic 32) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:176 — HiveTableOperations.doCommit has cyclomatic complexity 32 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · AbstractDeltaCatalog.createDeltaTable (cyclomatic 31) · ×1

AbstractDeltaCatalog.createDeltaTable (cyclomatic 31) spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:220 — AbstractDeltaCatalog.createDeltaTable has cyclomatic complexity 31 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ParquetStatsReader.decodeMinMaxStat (cyclomatic 30) · ×1

ParquetStatsReader.decodeMinMaxStat (cyclomatic 30) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetStatsReader.java:134 — ParquetStatsReader.decodeMinMaxStat has cyclomatic complexity 30 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cyclomatic 30) · ×1

ExpressionUtils.convertSparkFilterToKernelPredicate (cyclomatic 30) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:120 — ExpressionUtils.convertSparkFilterToKernelPredicate has cyclomatic complexity 30 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SchemaMergingUtils.mergeDataTypes (cyclomatic 28) · ×1

SchemaMergingUtils.mergeDataTypes (cyclomatic 28) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaMergingUtils.scala:193 — SchemaMergingUtils.mergeDataTypes has cyclomatic complexity 28 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · StatsCollector.aggMaxOrMin (cyclomatic 28) · ×1

StatsCollector.aggMaxOrMin (cyclomatic 28) spark/src/main/scala/org/apache/spark/sql/delta/stats/StatsCollectionUtils.scala:492 — StatsCollector.aggMaxOrMin has cyclomatic complexity 28 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · IcebergConverter.runIcebergConversionForActions (cyclomatic 27) · ×1

IcebergConverter.runIcebergConversionForActions (cyclomatic 27) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala:789 — IcebergConverter.runIcebergConversionForActions has cyclomatic complexity 27 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · GeneratedColumn.getOptimizablePartitionExpressions (cyclomatic 27) · ×1

GeneratedColumn.getOptimizablePartitionExpressions (cyclomatic 27) spark/src/main/scala/org/apache/spark/sql/delta/GeneratedColumn.scala:350 — GeneratedColumn.getOptimizablePartitionExpressions has cyclomatic complexity 27 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · OptimisticTransactionImpl.updateMetadataInternal (cyclomatic 26) · ×1

OptimisticTransactionImpl.updateMetadataInternal (cyclomatic 26) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:698 — OptimisticTransactionImpl.updateMetadataInternal has cyclomatic complexity 26 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ChecksumUtils.buildCrcInfoIncrementally (cyclomatic 26) · ×1

ChecksumUtils.buildCrcInfoIncrementally (cyclomatic 26) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java:376 — ChecksumUtils.buildCrcInfoIncrementally has cyclomatic complexity 26 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · CDCReaderImpl.changesToDF (cyclomatic 25) · ×1

CDCReaderImpl.changesToDF (cyclomatic 25) spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:230 — CDCReaderImpl.changesToDF has cyclomatic complexity 25 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · UCCommitCoordinatorClient.commitImpl (cyclomatic 25) · ×1

UCCommitCoordinatorClient.commitImpl (cyclomatic 25) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:325 — UCCommitCoordinatorClient.commitImpl has cyclomatic complexity 25 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cyclomatic 25) · ×1

DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cyclomatic 25) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1808 — DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles has cyclomatic complexity 25 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · get_spark_version_info.main (cyclomatic 24) · ×1

get_spark_version_info.main (cyclomatic 24) project/scripts/get_spark_version_info.py:239 — get_spark_version_info.main has cyclomatic complexity 24 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · Schema.stringToLiteral (cyclomatic 23) · ×1

Schema.stringToLiteral (cyclomatic 23) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:235 — Schema.stringToLiteral has cyclomatic complexity 23 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · RecordChecksum.computeNewChecksum (cyclomatic 23) · ×1

RecordChecksum.computeNewChecksum (cyclomatic 23) spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala:353 — RecordChecksum.computeNewChecksum has cyclomatic complexity 23 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · DeltaColumnDefaults.isLiteral (cyclomatic 23) · ×1

DeltaColumnDefaults.isLiteral (cyclomatic 23) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:105 — DeltaColumnDefaults.isLiteral has cyclomatic complexity 23 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cyclomatic 23) · ×1

MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cyclomatic 23) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java:602 — MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges has cyclomatic complexity 23 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · ConflictChecker.trackDataChange (cyclomatic 22) · ×1

ConflictChecker.trackDataChange (cyclomatic 22) spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:1599 — ConflictChecker.trackDataChange has cyclomatic complexity 22 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · UpdateExpressionsSupport.castIfNeeded (cyclomatic 22) · ×1

UpdateExpressionsSupport.castIfNeeded (cyclomatic 22) spark/src/main/scala/org/apache/spark/sql/delta/UpdateExpressionsSupport.scala:118 — UpdateExpressionsSupport.castIfNeeded has cyclomatic complexity 22 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · AutoCompactUtils.reserveTablePartitions (cyclomatic 22) · ×1

AutoCompactUtils.reserveTablePartitions (cyclomatic 22) spark/src/main/scala/org/apache/spark/sql/delta/hooks/AutoCompactUtils.scala:113 — AutoCompactUtils.reserveTablePartitions has cyclomatic complexity 22 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal (cyclomatic 22) · ×1

ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal (cyclomatic 22) kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/ProtocolMetadataLogReplay.java:96 — ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal has cyclomatic complexity 22 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DataFileStatistics.writeJsonValue (cyclomatic 22) · ×1

DataFileStatistics.writeJsonValue (cyclomatic 22) kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:391 — DataFileStatistics.writeJsonValue has cyclomatic complexity 22 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · FlinkUnityCatalogTable.fromJson (cyclomatic 22) · ×1

FlinkUnityCatalogTable.fromJson (cyclomatic 22) flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java:129 — FlinkUnityCatalogTable.fromJson has cyclomatic complexity 22 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · IcebergCompatBase.enforceInvariantsAndDependencies (cyclomatic 21) · ×1

IcebergCompatBase.enforceInvariantsAndDependencies (cyclomatic 21) spark/src/main/scala/org/apache/spark/sql/delta/IcebergCompat.scala:216 — IcebergCompatBase.enforceInvariantsAndDependencies has cyclomatic complexity 21 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · OptimisticTransactionImpl.prepareInitialActions (cyclomatic 21) · ×1

OptimisticTransactionImpl.prepareInitialActions (cyclomatic 21) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2582 — OptimisticTransactionImpl.prepareInitialActions has cyclomatic complexity 21 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DeltaSourceUtils.translateFilters (cyclomatic 21) · ×1

DeltaSourceUtils.translateFilters (cyclomatic 21) spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceUtils.scala:74 — DeltaSourceUtils.translateFilters has cyclomatic complexity 21 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · ParquetSchemaUtils.toParquetType (cyclomatic 21) · ×1

ParquetSchemaUtils.toParquetType (cyclomatic 21) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:302 — ParquetSchemaUtils.toParquetType has cyclomatic complexity 21 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cyclomatic 21) · ×1

DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cyclomatic 21) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1253 — DeltaV2MicroBatchStream.validateCommitAndDecideSkipping has cyclomatic complexity 21 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · Schema.unescapeString (cyclomatic 20) · ×1

Schema.unescapeString (cyclomatic 20) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:177 — Schema.unescapeString has cyclomatic complexity 20 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SparkToIcebergExpressionConverter.convert (cyclomatic 20) · ×1

SparkToIcebergExpressionConverter.convert (cyclomatic 20) iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/SparkToIcebergExpressionConverter.scala:73 — SparkToIcebergExpressionConverter.convert has cyclomatic complexity 20 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · DeltaColumnDefaults.unescapeString (cyclomatic 20) · ×1

DeltaColumnDefaults.unescapeString (cyclomatic 20) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:53 — DeltaColumnDefaults.unescapeString has cyclomatic complexity 20 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · PreprocessTableMerge.apply (cyclomatic 20) · ×1

PreprocessTableMerge.apply (cyclomatic 20) spark/src/main/scala/org/apache/spark/sql/delta/PreprocessTableMerge.scala:50 — PreprocessTableMerge.apply has cyclomatic complexity 20 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ClassicMergeExecutor.writeAllChanges (cyclomatic 20) · ×1

ClassicMergeExecutor.writeAllChanges (cyclomatic 20) spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/ClassicMergeExecutor.scala:288 — ClassicMergeExecutor.writeAllChanges has cyclomatic complexity 20 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · MumblingBitmapWriter.merge (cyclomatic 20) · ×1

MumblingBitmapWriter.merge (cyclomatic 20) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/MumblingBitmapWriter.java:111 — MumblingBitmapWriter.merge has cyclomatic complexity 20 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DeltaTableBuilder.addColumn (cyclomatic 20) · ×1

DeltaTableBuilder.addColumn (cyclomatic 20) python/delta/connect/tables.py:666 — DeltaTableBuilder.addColumn has cyclomatic complexity 20 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · CreateDeltaTableCommand.getOperation (cyclomatic 19) · ×1

CreateDeltaTableCommand.getOperation (cyclomatic 19) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:758 — CreateDeltaTableCommand.getOperation has cyclomatic complexity 19 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SchemaUtils.reportDifferencesByCategory (cyclomatic 19) · ×1

SchemaUtils.reportDifferencesByCategory (cyclomatic 19) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala:645 — SchemaUtils.reportDifferencesByCategory has cyclomatic complexity 19 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages. This is NOT this file's highest cyclomatic complexity: SchemaUtils.findUnsupportedDataTypesRecursively (cyclomatic 24) is higher and carries no row of its own — it was excluded as a flat dispatcher (a long switch/match over independent cases: many branches, almost no nesting), which this dimension does not treat as a refactor obligation. It is named here so the ranking you see in this file is not mistaken for the whole of it; the excluded method is counted neither in this dimension's figures nor in its score.

D1 · Cyclomatic Complexity · ParquetColumnWriters.createColumnWriter (cyclomatic 19) · ×1

ParquetColumnWriters.createColumnWriter (cyclomatic 19) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnWriters.java:94 — ParquetColumnWriters.createColumnWriter has cyclomatic complexity 19 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · CommitRangeBuilderImpl.validateInputOnBuild (cyclomatic 19) · ×1

CommitRangeBuilderImpl.validateInputOnBuild (cyclomatic 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/commitrange/CommitRangeBuilderImpl.java:93 — CommitRangeBuilderImpl.validateInputOnBuild has cyclomatic complexity 19 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SnapshotManager.buildLogSegmentFromStartCheckpointVersion (cyclomatic 19) · ×1

SnapshotManager.buildLogSegmentFromStartCheckpointVersion (cyclomatic 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java:313 — SnapshotManager.buildLogSegmentFromStartCheckpointVersion has cyclomatic complexity 19 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · DataTypeJsonSerDe.writeFieldMetadata (cyclomatic 19) · ×1

DataTypeJsonSerDe.writeFieldMetadata (cyclomatic 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:633 — DataTypeJsonSerDe.writeFieldMetadata has cyclomatic complexity 19 (threshold 15). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.

D1 · Cyclomatic Complexity · DeltaLogActionUtils.listDeltaLogFilesAsIter (cyclomatic 19) · ×1

DeltaLogActionUtils.listDeltaLogFilesAsIter (cyclomatic 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaLogActionUtils.java:148 — DeltaLogActionUtils.listDeltaLogFilesAsIter has cyclomatic complexity 19 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions (cyclomatic 18) · ×1

DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions (cyclomatic 18) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:549 — DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SchemaUtils.isReadCompatible (cyclomatic 18) · ×1

SchemaUtils.isReadCompatible (cyclomatic 18) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala:538 — SchemaUtils.isReadCompatible has cyclomatic complexity 18 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions. This is NOT this file's highest cyclomatic complexity: SchemaUtils.findUnsupportedDataTypesRecursively (cyclomatic 24) is higher and carries no row of its own — it was excluded as a flat dispatcher (a long switch/match over independent cases: many branches, almost no nesting), which this dimension does not treat as a refactor obligation. It is named here so the ranking you see in this file is not mistaken for the whole of it; the excluded method is counted neither in this dimension's figures nor in its score.

D1 · Cyclomatic Complexity · DeltaSource.validateCommitAndDecideSkipping (cyclomatic 18) · ×1

DeltaSource.validateCommitAndDecideSkipping (cyclomatic 18) spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala:1030 — DeltaSource.validateCommitAndDecideSkipping has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · UnityCatalogUtils.toUCTypeName (cyclomatic 18) · ×1

UnityCatalogUtils.toUCTypeName (cyclomatic 18) kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/UnityCatalogUtils.java:325 — UnityCatalogUtils.toUCTypeName has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ColumnDefaults.validateLiteral (cyclomatic 18) · ×1

ColumnDefaults.validateLiteral (cyclomatic 18) kernel/kernel-api/src/main/java/io/delta/kernel/internal/columndefaults/ColumnDefaults.java:133 — ColumnDefaults.validateLiteral has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · DataTypeJsonSerDe.parseFieldMetadata (cyclomatic 18) · ×1

DataTypeJsonSerDe.parseFieldMetadata (cyclomatic 18) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:372 — DataTypeJsonSerDe.parseFieldMetadata has cyclomatic complexity 18 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · SparkRowToKernelRow.sparkValueToKernel (cyclomatic 18) · ×1

SparkRowToKernelRow.sparkValueToKernel (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java:272 — SparkRowToKernelRow.sparkValueToKernel has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cyclomatic 18) · ×1

SchemaUtils.convertKernelDataTypeToSparkDataType (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:75 — SchemaUtils.convertKernelDataTypeToSparkDataType has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages. This shape REPEATS in the file: one other method here (SchemaUtils.convertSparkDataTypeToKernelDataType) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D1 · Cyclomatic Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cyclomatic 18) · ×1

SchemaUtils.convertSparkDataTypeToKernelDataType (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:210 — SchemaUtils.convertSparkDataTypeToKernelDataType has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages. This shape REPEATS in the file: one other method here (SchemaUtils.convertKernelDataTypeToSparkDataType) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D1 · Cyclomatic Complexity · KernelRowToSparkRow.toSparkValue (cyclomatic 18) · ×1

KernelRowToSparkRow.toSparkValue (cyclomatic 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:315 — KernelRowToSparkRow.toSparkValue has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · IcebergStatsUtils.icebergStatsToDelta (cyclomatic 17) · ×1

IcebergStatsUtils.icebergStatsToDelta (cyclomatic 17) iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergStatsUtils.scala:199 — IcebergStatsUtils.icebergStatsToDelta has cyclomatic complexity 17 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · DeltaSharingJsonPredicates.toExpression (cyclomatic 17) · ×1

DeltaSharingJsonPredicates.toExpression (cyclomatic 17) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingJsonPredicates.scala:166 — DeltaSharingJsonPredicates.toExpression has cyclomatic complexity 17 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · DeltaCommandPlugin.processCreateDeltaTable (cyclomatic 17) · ×1

DeltaCommandPlugin.processCreateDeltaTable (cyclomatic 17) spark-connect/server/src/main/scala/io/delta/connect/DeltaCommandPlugin.scala:117 — DeltaCommandPlugin.processCreateDeltaTable has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DeltaAnalysis.resolveCloneCommand (cyclomatic 17) · ×1

DeltaAnalysis.resolveCloneCommand (cyclomatic 17) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:868 — DeltaAnalysis.resolveCloneCommand has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · ImplicitMetadataOperation.updateMetadata (cyclomatic 17) · ×1

ImplicitMetadataOperation.updateMetadata (cyclomatic 17) spark/src/main/scala/org/apache/spark/sql/delta/schema/ImplicitMetadataOperation.scala:69 — ImplicitMetadataOperation.updateMetadata has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · ParquetColumnReaders.createConverter (cyclomatic 17) · ×1

ParquetColumnReaders.createConverter (cyclomatic 17) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:38 — ParquetColumnReaders.createConverter has cyclomatic complexity 17 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · SchemaUtils.validateFieldCompatibility (cyclomatic 17) · ×1

SchemaUtils.validateFieldCompatibility (cyclomatic 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:667 — SchemaUtils.validateFieldCompatibility has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · VectorUtils.getValueAsObject (cyclomatic 17) · ×1

VectorUtils.getValueAsObject (cyclomatic 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/VectorUtils.java:138 — VectorUtils.getValueAsObject has cyclomatic complexity 17 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · DeltaHistoryManager.getEarliestRecreatableCommit (cyclomatic 17) · ×1

DeltaHistoryManager.getEarliestRecreatableCommit (cyclomatic 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaHistoryManager.java:371 — DeltaHistoryManager.getEarliestRecreatableCommit has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · TransactionImpl.doCommit (cyclomatic 17) · ×1

TransactionImpl.doCommit (cyclomatic 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java:508 — TransactionImpl.doCommit has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · UnityCatalogTableOperations.doCommit (cyclomatic 17) · ×1

UnityCatalogTableOperations.doCommit (cyclomatic 17) icebergShaded/src/main/java/org/apache/iceberg/unityCatalog/UnityCatalogTableOperations.java:88 — UnityCatalogTableOperations.doCommit has cyclomatic complexity 17 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · DeltaInsertCastSupport.addCastToColumn (cyclomatic 16) · ×1

DeltaInsertCastSupport.addCastToColumn (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/DeltaInsertCastSupport.scala:163 — DeltaInsertCastSupport.addCastToColumn has cyclomatic complexity 16 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · GeneratedColumn.generatePartitionFilters (cyclomatic 16) · ×1

GeneratedColumn.generatePartitionFilters (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/GeneratedColumn.scala:653 — GeneratedColumn.generatePartitionFilters has cyclomatic complexity 16 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · OptimisticTransactionImpl.commitImpl (cyclomatic 16) · ×1

OptimisticTransactionImpl.commitImpl (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:1919 — OptimisticTransactionImpl.commitImpl has cyclomatic complexity 16 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · CreateDeltaTableCommand.handleCreateTable (cyclomatic 16) · ×1

CreateDeltaTableCommand.handleCreateTable (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:398 — CreateDeltaTableCommand.handleCreateTable has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · Constraints.validateCheckConstraintsInternal (cyclomatic 16) · ×1

Constraints.validateCheckConstraintsInternal (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/constraints/Constraints.scala:180 — Constraints.validateCheckConstraintsInternal has cyclomatic complexity 16 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.

D1 · Cyclomatic Complexity · TransactionalWrite.writeFiles (cyclomatic 16) · ×1

TransactionalWrite.writeFiles (cyclomatic 16) spark/src/main/scala/org/apache/spark/sql/delta/files/TransactionalWrite.scala:406 — TransactionalWrite.writeFiles has cyclomatic complexity 16 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function so the top-level body reads as a short sequence of named decisions.

D1 · Cyclomatic Complexity · GenericColumnVector.extractTypedValue (cyclomatic 16) · ×1

GenericColumnVector.extractTypedValue (cyclomatic 16) kernel/kernel-api/src/main/java/io/delta/kernel/internal/data/GenericColumnVector.java:172 — GenericColumnVector.extractTypedValue has cyclomatic complexity 16 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D1 · Cyclomatic Complexity · ActiveAddFilesIterator.prepareNext (cyclomatic 16) · ×1

ActiveAddFilesIterator.prepareNext (cyclomatic 16) kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/ActiveAddFilesIterator.java:146 — ActiveAddFilesIterator.prepareNext has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.

D1 · Cyclomatic Complexity · PartitionUtils.convertRowValueToKernelLiteral (cyclomatic 16) · ×1

PartitionUtils.convertRowValueToKernelLiteral (cyclomatic 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:338 — PartitionUtils.convertRowValueToKernelLiteral has cyclomatic complexity 16 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · VariantStatsData.forPrefixAndStatType (cognitive 173) · ×1

VariantStatsData.forPrefixAndStatType (cognitive 173) spark/src/main/scala/org/apache/spark/sql/delta/stats/VariantStats.scala:169 — VariantStatsData.forPrefixAndStatType has cognitive complexity 173 (threshold 15). Drivers by points: match/switch 20 (92 pts), if/else 34 (73 pts), boolean chains 6, loops 1 (2 pts) (nesting depth added 112). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · DeltaAnalysis.apply (cognitive 152) · ×1

DeltaAnalysis.apply (cognitive 152) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:90 — DeltaAnalysis.apply has cognitive complexity 152 (threshold 15). Drivers by points: if/else 54 (84 pts), match/switch 21 (45 pts), boolean chains 14, error handling 3 (9 pts) (nesting depth added 60). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · ExpressionUtils.dsv2PredicateToCatalystExpression (cognitive 107) · ×1

ExpressionUtils.dsv2PredicateToCatalystExpression (cognitive 107) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:572 — ExpressionUtils.dsv2PredicateToCatalystExpression has cognitive complexity 107 (threshold 15). Drivers by points: if/else 36 (90 pts), boolean chains 12, loops 1 (4 pts), match/switch 1 (nesting depth added 57). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · WriteIntoDelta.writeAndReturnCommitData (cognitive 96) · ×1

WriteIntoDelta.writeAndReturnCommitData (cognitive 96) spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDelta.scala:136 — WriteIntoDelta.writeAndReturnCommitData has cognitive complexity 96 (threshold 15). Drivers by points: if/else 43 (57 pts), boolean chains 18, match/switch 8 (17 pts), error handling 2 (4 pts) (nesting depth added 25). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · IntervalParser.toMicroSeconds (cognitive 83) · ×1

IntervalParser.toMicroSeconds (cognitive 83) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/IntervalParserUtils.java:110 — IntervalParser.toMicroSeconds has cognitive complexity 83 (threshold 15). Drivers by points: if/else 35 (59 pts), boolean chains 13, error handling 2 (7 pts), match/switch 2 (3 pts), loops 1 (nesting depth added 30). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · JsonUtils.parseJsonValueToLiteral (cognitive 68) · ×1

JsonUtils.parseJsonValueToLiteral (cognitive 68) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/JsonUtils.java:115 — JsonUtils.parseJsonValueToLiteral has cognitive complexity 68 (threshold 15). Drivers by points: if/else 37 (56 pts), match/switch 2 (6 pts), ternaries 1 (3 pts), boolean chains 2, error handling 1 (nesting depth added 25). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cognitive 56) · ×1

DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles (cognitive 56) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1808 — DeltaV2MicroBatchStream.collectAndBuildCDCIndexedFiles has cognitive complexity 56 (threshold 15). Drivers by points: if/else 17 (39 pts), loops 6 (14 pts), ternaries 2, boolean chains 1 (nesting depth added 30). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DefaultJsonRow.decodeElement (cognitive 54) · ×1

DefaultJsonRow.decodeElement (cognitive 54) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultJsonRow.java:136 — DefaultJsonRow.decodeElement has cognitive complexity 54 (threshold 15). Drivers by points: if/else 23 (33 pts), match/switch 4 (10 pts), boolean chains 7, loops 2 (4 pts) (nesting depth added 18). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal (cognitive 53) · ×1

ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal (cognitive 53) kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/ProtocolMetadataLogReplay.java:96 — ProtocolMetadataLogReplay.loadProtocolAndMetadataInternal has cognitive complexity 53 (threshold 15). Drivers by points: if/else 15 (43 pts), loops 3 (7 pts), boolean chains 2, error handling 1 (nesting depth added 32). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · Schema.unescapeString (cognitive 51) · ×1

Schema.unescapeString (cognitive 51) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:177 — Schema.unescapeString has cognitive complexity 51 (threshold 15). Drivers by points: if/else 23 (45 pts), boolean chains 5, loops 1 (nesting depth added 22). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaColumnDefaults.unescapeString (cognitive 51) · ×1

DeltaColumnDefaults.unescapeString (cognitive 51) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:53 — DeltaColumnDefaults.unescapeString has cognitive complexity 51 (threshold 15). Drivers by points: if/else 23 (45 pts), boolean chains 5, loops 1 (nesting depth added 22). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ChecksumUtils.buildCrcInfoIncrementally (cognitive 50) · ×1

ChecksumUtils.buildCrcInfoIncrementally (cognitive 50) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checksum/ChecksumUtils.java:376 — ChecksumUtils.buildCrcInfoIncrementally has cognitive complexity 50 (threshold 15). Drivers by points: if/else 15 (34 pts), boolean chains 7, ternaries 2 (6 pts), loops 2 (3 pts) (nesting depth added 24). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UCCommitCoordinatorClient.commitImpl (cognitive 49) · ×1

UCCommitCoordinatorClient.commitImpl (cognitive 49) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:325 — UCCommitCoordinatorClient.commitImpl has cognitive complexity 49 (threshold 15). Drivers by points: error handling 15 (27 pts), if/else 9 (20 pts), boolean chains 1, loops 1 (nesting depth added 23). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · AbstractDeltaCatalog.alterTable (cognitive 46) · ×1

AbstractDeltaCatalog.alterTable (cognitive 46) spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:1175 — AbstractDeltaCatalog.alterTable has cognitive complexity 46 (threshold 15). Drivers by points: if/else 19 (30 pts), match/switch 10 (15 pts), boolean chains 1 (nesting depth added 16). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · HiveTableOperations.doCommit (cognitive 46) · ×1

HiveTableOperations.doCommit (cognitive 46) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveTableOperations.java:176 — HiveTableOperations.doCommit has cognitive complexity 46 (threshold 15). Drivers by points: if/else 15 (25 pts), error handling 8, loops 2 (5 pts), boolean chains 3, ternaries 3, match/switch 1 (2 pts) (nesting depth added 14). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeleteCommand.performDelete (cognitive 45) · ×1

DeleteCommand.performDelete (cognitive 45) spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:167 — DeleteCommand.performDelete has cognitive complexity 45 (threshold 15). Drivers by points: if/else 19 (44 pts), match/switch 1 (nesting depth added 25). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cognitive 45) · ×1

MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges (cognitive 45) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/MetadataEvolutionHandler.java:602 — MetadataEvolutionHandler.getMergedConsecutiveMetadataChanges has cognitive complexity 45 (threshold 15). Drivers by points: if/else 8 (21 pts), ternaries 3 (9 pts), loops 3 (6 pts), boolean chains 5, error handling 3 (4 pts) (nesting depth added 23). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · get_spark_version_info.main (cognitive 43) · ×1

get_spark_version_info.main (cognitive 43) project/scripts/get_spark_version_info.py:239 — get_spark_version_info.main has cognitive complexity 43 (threshold 15). Drivers by points: if/else 13 (26 pts), loops 4 (8 pts), ternaries 2 (8 pts), error handling 1 (nesting depth added 23). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ParquetStatsReader.decodeMinMaxStat (cognitive 41) · ×1

ParquetStatsReader.decodeMinMaxStat (cognitive 41) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetStatsReader.java:134 — ParquetStatsReader.decodeMinMaxStat has cognitive complexity 41 (threshold 15). Drivers by points: if/else 21 (24 pts), ternaries 7 (15 pts), boolean chains 2 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · IcebergConverter.runIcebergConversionForActions (cognitive 40) · ×1

IcebergConverter.runIcebergConversionForActions (cognitive 40) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/IcebergConverter.scala:789 — IcebergConverter.runIcebergConversionForActions has cognitive complexity 40 (threshold 15). Drivers by points: if/else 13 (27 pts), match/switch 5 (12 pts), boolean chains 1 (nesting depth added 21). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · OptimisticTransactionImpl.updateMetadataInternal (cognitive 39) · ×1

OptimisticTransactionImpl.updateMetadataInternal (cognitive 39) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:698 — OptimisticTransactionImpl.updateMetadataInternal has cognitive complexity 39 (threshold 15). Drivers by points: if/else 25 (32 pts), boolean chains 7 (nesting depth added 7). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · CreateDeltaTableCommand.getOperation (cognitive 38) · ×1

CreateDeltaTableCommand.getOperation (cognitive 38) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:758 — CreateDeltaTableCommand.getOperation has cognitive complexity 38 (threshold 15). Drivers by points: if/else 24 (36 pts), boolean chains 1, match/switch 1 (nesting depth added 12). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · MumblingBitmapWriter.merge (cognitive 38) · ×1

MumblingBitmapWriter.merge (cognitive 38) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/MumblingBitmapWriter.java:111 — MumblingBitmapWriter.merge has cognitive complexity 38 (threshold 15). Drivers by points: loops 6 (13 pts), if/else 6 (11 pts), ternaries 4 (10 pts), boolean chains 4 (nesting depth added 18). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ExpressionUtils.convertSparkFilterToKernelPredicate (cognitive 38) · ×1

ExpressionUtils.convertSparkFilterToKernelPredicate (cognitive 38) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:120 — ExpressionUtils.convertSparkFilterToKernelPredicate has cognitive complexity 38 (threshold 15). Drivers by points: if/else 21 (28 pts), boolean chains 6, loops 1 (2 pts), ternaries 1 (2 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cognitive 38) · ×1

DeltaV2MicroBatchStream.validateCommitAndDecideSkipping (cognitive 38) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1253 — DeltaV2MicroBatchStream.validateCommitAndDecideSkipping has cognitive complexity 38 (threshold 15). Drivers by points: if/else 11 (26 pts), boolean chains 5, loops 2 (3 pts), ternaries 1 (3 pts), error handling 1 (nesting depth added 18). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataSkippingUtils.constructDataSkippingFilter (cognitive 37) · ×1

DataSkippingUtils.constructDataSkippingFilter (cognitive 37) kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:157 — DataSkippingUtils.constructDataSkippingFilter has cognitive complexity 37 (threshold 15). Drivers by points: if/else 15 (30 pts), boolean chains 6, match/switch 1 (nesting depth added 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · CDCReaderImpl.changesToDF (cognitive 36) · ×1

CDCReaderImpl.changesToDF (cognitive 36) spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReader.scala:230 — CDCReaderImpl.changesToDF has cognitive complexity 36 (threshold 15). Drivers by points: if/else 16 (19 pts), match/switch 7 (12 pts), boolean chains 5 (nesting depth added 8). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · IcebergCompatBase.enforceInvariantsAndDependencies (cognitive 35) · ×1

IcebergCompatBase.enforceInvariantsAndDependencies (cognitive 35) spark/src/main/scala/org/apache/spark/sql/delta/IcebergCompat.scala:216 — IcebergCompatBase.enforceInvariantsAndDependencies has cognitive complexity 35 (threshold 15). Drivers by points: if/else 11 (23 pts), match/switch 4 (7 pts), boolean chains 5 (nesting depth added 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · StatsCollector.aggMaxOrMin (cognitive 34) · ×1

StatsCollector.aggMaxOrMin (cognitive 34) spark/src/main/scala/org/apache/spark/sql/delta/stats/StatsCollectionUtils.scala:492 — StatsCollector.aggMaxOrMin has cognitive complexity 34 (threshold 15). Drivers by points: if/else 16 (24 pts), boolean chains 7, match/switch 2 (3 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UpdateExpressionsSupport.castIfNeeded (cognitive 33) · ×1

UpdateExpressionsSupport.castIfNeeded (cognitive 33) spark/src/main/scala/org/apache/spark/sql/delta/UpdateExpressionsSupport.scala:118 — UpdateExpressionsSupport.castIfNeeded has cognitive complexity 33 (threshold 15). Drivers by points: if/else 10 (22 pts), match/switch 3 (6 pts), boolean chains 5 (nesting depth added 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · ColumnWithDefaultExprUtils.addDefaultExprsOrReturnConstraints (cognitive 31) · ×1

ColumnWithDefaultExprUtils.addDefaultExprsOrReturnConstraints (cognitive 31) spark/src/main/scala/org/apache/spark/sql/delta/ColumnWithDefaultExprUtils.scala:113 — ColumnWithDefaultExprUtils.addDefaultExprsOrReturnConstraints has cognitive complexity 31 (threshold 15). Drivers by points: if/else 14 (22 pts), match/switch 4 (6 pts), error handling 1 (2 pts), boolean chains 1 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UpdateExpressionsSupport.generateUpdateExpressions (cognitive 31) · ×1

UpdateExpressionsSupport.generateUpdateExpressions (cognitive 31) spark/src/main/scala/org/apache/spark/sql/delta/UpdateExpressionsSupport.scala:452 — UpdateExpressionsSupport.generateUpdateExpressions has cognitive complexity 31 (threshold 15). Drivers by points: if/else 15 (23 pts), match/switch 2 (7 pts), boolean chains 1 (nesting depth added 13). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · AbstractDeltaCatalog.createDeltaTable (cognitive 31) · ×1

AbstractDeltaCatalog.createDeltaTable (cognitive 31) spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:220 — AbstractDeltaCatalog.createDeltaTable has cognitive complexity 31 (threshold 15). Drivers by points: if/else 19 (20 pts), boolean chains 8, match/switch 3 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · ConflictChecker.trackDataChange (cognitive 30) · ×1

ConflictChecker.trackDataChange (cognitive 30) spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:1599 — ConflictChecker.trackDataChange has cognitive complexity 30 (threshold 15). Drivers by points: if/else 11 (18 pts), boolean chains 10, match/switch 2 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ClassicMergeExecutor.writeAllChanges (cognitive 30) · ×1

ClassicMergeExecutor.writeAllChanges (cognitive 30) spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/ClassicMergeExecutor.scala:288 — ClassicMergeExecutor.writeAllChanges has cognitive complexity 30 (threshold 15). Drivers by points: if/else 24 (26 pts), boolean chains 3, match/switch 1 (nesting depth added 2). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · CommitRangeBuilderImpl.validateInputOnBuild (cognitive 30) · ×1

CommitRangeBuilderImpl.validateInputOnBuild (cognitive 30) kernel/kernel-api/src/main/java/io/delta/kernel/internal/commitrange/CommitRangeBuilderImpl.java:93 — CommitRangeBuilderImpl.validateInputOnBuild has cognitive complexity 30 (threshold 15). Drivers by points: if/else 14 (26 pts), boolean chains 4 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataTypeJsonSerDe.writeFieldMetadata (cognitive 30) · ×1

DataTypeJsonSerDe.writeFieldMetadata (cognitive 30) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:633 — DataTypeJsonSerDe.writeFieldMetadata has cognitive complexity 30 (threshold 15). Drivers by points: loops 6 (16 pts), if/else 13 (14 pts) (nesting depth added 11). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.

D2 · Cognitive Complexity · OptimisticTransactionImpl.prepareInitialActions (cognitive 29) · ×1

OptimisticTransactionImpl.prepareInitialActions (cognitive 29) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2582 — OptimisticTransactionImpl.prepareInitialActions has cognitive complexity 29 (threshold 15). Drivers by points: if/else 14 (22 pts), match/switch 4, boolean chains 3 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SchemaUtils.computeSchemaChangesById (cognitive 29) · ×1

SchemaUtils.computeSchemaChangesById (cognitive 29) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:379 — SchemaUtils.computeSchemaChangesById has cognitive complexity 29 (threshold 15). Drivers by points: if/else 11 (26 pts), boolean chains 2, loops 1 (nesting depth added 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SchemaUtils.validateFieldCompatibility (cognitive 29) · ×1

SchemaUtils.validateFieldCompatibility (cognitive 29) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/SchemaUtils.java:667 — SchemaUtils.validateFieldCompatibility has cognitive complexity 29 (threshold 15). Drivers by points: if/else 9 (20 pts), boolean chains 7, loops 1 (2 pts) (nesting depth added 12). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · spark_structured_logging_style.main (cognitive 29) · ×1

spark_structured_logging_style.main (cognitive 29) dev/spark_structured_logging_style.py:42 — spark_structured_logging_style.main has cognitive complexity 29 (threshold 15). Drivers by points: if/else 6 (15 pts), loops 6 (13 pts), boolean chains 1 (nesting depth added 16). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · MergeOutputGeneration.generateAllActionExprs (cognitive 28) · ×1

MergeOutputGeneration.generateAllActionExprs (cognitive 28) spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/MergeOutputGeneration.scala:262 — MergeOutputGeneration.generateAllActionExprs has cognitive complexity 28 (threshold 15). Drivers by points: if/else 18 (27 pts), match/switch 1 (nesting depth added 9). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · IndexedChangeFileSeq.filterFiles (cognitive 28) · ×1

IndexedChangeFileSeq.filterFiles (cognitive 28) spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceCDCSupport.scala:112 — IndexedChangeFileSeq.filterFiles has cognitive complexity 28 (threshold 15). Drivers by points: if/else 13 (21 pts), match/switch 2 (5 pts), boolean chains 2 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaHistoryManager.getEarliestRecreatableCommit (cognitive 28) · ×1

DeltaHistoryManager.getEarliestRecreatableCommit (cognitive 28) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaHistoryManager.java:371 — DeltaHistoryManager.getEarliestRecreatableCommit has cognitive complexity 28 (threshold 15). Drivers by points: if/else 12 (22 pts), boolean chains 4, error handling 1, loops 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ModularSuiteGenerator.generateSuites (cognitive 27) · ×1

ModularSuiteGenerator.generateSuites (cognitive 27) spark/delta-suite-generator/src/main/scala/io/delta/suitegenerator/ModularSuiteGenerator.scala:78 — ModularSuiteGenerator.generateSuites has cognitive complexity 27 (threshold 15). Drivers by points: loops 6 (21 pts), if/else 2 (6 pts) (nesting depth added 19). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.

D2 · Cognitive Complexity · SchemaUtils.reportDifferencesByCategory (cognitive 27) · ×1

SchemaUtils.reportDifferencesByCategory (cognitive 27) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala:645 — SchemaUtils.reportDifferencesByCategory has cognitive complexity 27 (threshold 15). Drivers by points: if/else 24 (26 pts), match/switch 1 (nesting depth added 2). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · ActiveAddFilesIterator.prepareNext (cognitive 27) · ×1

ActiveAddFilesIterator.prepareNext (cognitive 27) kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/ActiveAddFilesIterator.java:146 — ActiveAddFilesIterator.prepareNext has cognitive complexity 27 (threshold 15). Drivers by points: if/else 14 (24 pts), loops 2 (3 pts) (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaLogActionUtils.listDeltaLogFilesAsIter (cognitive 27) · ×1

DeltaLogActionUtils.listDeltaLogFilesAsIter (cognitive 27) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaLogActionUtils.java:148 — DeltaLogActionUtils.listDeltaLogFilesAsIter has cognitive complexity 27 (threshold 15). Drivers by points: if/else 15 (21 pts), boolean chains 6 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · RecordChecksum.computeNewChecksum (cognitive 26) · ×1

RecordChecksum.computeNewChecksum (cognitive 26) spark/src/main/scala/org/apache/spark/sql/delta/Checksum.scala:353 — RecordChecksum.computeNewChecksum has cognitive complexity 26 (threshold 15). Drivers by points: if/else 15 (16 pts), boolean chains 5, match/switch 3 (5 pts) (nesting depth added 3). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · OptimisticTransactionImpl.doCommitRetryIteratively (cognitive 26) · ×1

OptimisticTransactionImpl.doCommitRetryIteratively (cognitive 26) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2848 — OptimisticTransactionImpl.doCommitRetryIteratively has cognitive complexity 26 (threshold 15). Drivers by points: if/else 5 (11 pts), error handling 4 (8 pts), boolean chains 3, match/switch 1 (3 pts), loops 1 (nesting depth added 12). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataTypeJsonSerDe.parseFieldMetadata (cognitive 26) · ×1

DataTypeJsonSerDe.parseFieldMetadata (cognitive 26) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:372 — DataTypeJsonSerDe.parseFieldMetadata has cognitive complexity 26 (threshold 15). Drivers by points: if/else 18 (24 pts), boolean chains 1, loops 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataFileStatistics.writeJsonValue (cognitive 26) · ×1

DataFileStatistics.writeJsonValue (cognitive 26) kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:391 — DataFileStatistics.writeJsonValue has cognitive complexity 26 (threshold 15). Drivers by points: if/else 21 (23 pts), boolean chains 3 (nesting depth added 2). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · DeltaColumnMappingBase.assignColumnIdAndPhysicalNameToSchema (cognitive 25) · ×1

DeltaColumnMappingBase.assignColumnIdAndPhysicalNameToSchema (cognitive 25) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnMapping.scala:437 — DeltaColumnMappingBase.assignColumnIdAndPhysicalNameToSchema has cognitive complexity 25 (threshold 15). Drivers by points: if/else 15 (22 pts), boolean chains 3 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · GeneratedColumn.getOptimizablePartitionExpressions (cognitive 25) · ×1

GeneratedColumn.getOptimizablePartitionExpressions (cognitive 25) spark/src/main/scala/org/apache/spark/sql/delta/GeneratedColumn.scala:350 — GeneratedColumn.getOptimizablePartitionExpressions has cognitive complexity 25 (threshold 15). Drivers by points: match/switch 5 (14 pts), if/else 11 (nesting depth added 9). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · PreprocessTableMerge.apply (cognitive 25) · ×1

PreprocessTableMerge.apply (cognitive 25) spark/src/main/scala/org/apache/spark/sql/delta/PreprocessTableMerge.scala:50 — PreprocessTableMerge.apply has cognitive complexity 25 (threshold 15). Drivers by points: if/else 13 (16 pts), match/switch 5 (6 pts), boolean chains 3 (nesting depth added 4). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions (cognitive 24) · ×1

DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions (cognitive 24) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:549 — DeltaSharingLogFileSystem.constructLocalDeltaLogAcrossVersions has cognitive complexity 24 (threshold 15). Drivers by points: if/else 16 (22 pts), loops 1, match/switch 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ConflictChecker.checkProtocolCompatibility (cognitive 24) · ×1

ConflictChecker.checkProtocolCompatibility (cognitive 24) spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:375 — ConflictChecker.checkProtocolCompatibility has cognitive complexity 24 (threshold 15). Drivers by points: if/else 11 (20 pts), match/switch 1 (3 pts), boolean chains 1 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaAnalysis.resolveCloneCommand (cognitive 24) · ×1

DeltaAnalysis.resolveCloneCommand (cognitive 24) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:868 — DeltaAnalysis.resolveCloneCommand has cognitive complexity 24 (threshold 15). Drivers by points: if/else 11 (17 pts), match/switch 3 (5 pts), error handling 1 (2 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaHistoryManager.getActiveCommitAtTime (cognitive 24) · ×1

DeltaHistoryManager.getActiveCommitAtTime (cognitive 24) spark/src/main/scala/org/apache/spark/sql/delta/DeltaHistoryManager.scala:303 — DeltaHistoryManager.getActiveCommitAtTime has cognitive complexity 24 (threshold 15). Drivers by points: if/else 16 (21 pts), boolean chains 3 (nesting depth added 5). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · AutoCompactUtils.reserveTablePartitions (cognitive 24) · ×1

AutoCompactUtils.reserveTablePartitions (cognitive 24) spark/src/main/scala/org/apache/spark/sql/delta/hooks/AutoCompactUtils.scala:113 — AutoCompactUtils.reserveTablePartitions has cognitive complexity 24 (threshold 15). Drivers by points: if/else 15 (16 pts), boolean chains 8 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · TransactionImpl.doCommit (cognitive 24) · ×1

TransactionImpl.doCommit (cognitive 24) kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java:508 — TransactionImpl.doCommit has cognitive complexity 24 (threshold 15). Drivers by points: if/else 11 (18 pts), boolean chains 3, ternaries 2, error handling 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SparkRowToKernelRow.sparkValueToKernel (cognitive 24) · ×1

SparkRowToKernelRow.sparkValueToKernel (cognitive 24) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SparkRowToKernelRow.java:272 — SparkRowToKernelRow.sparkValueToKernel has cognitive complexity 24 (threshold 15). Drivers by points: if/else 19 (24 pts) (nesting depth added 5). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · CreateDeltaTableCommand.verifyTableMetadata (cognitive 23) · ×1

CreateDeltaTableCommand.verifyTableMetadata (cognitive 23) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:668 — CreateDeltaTableCommand.verifyTableMetadata has cognitive complexity 23 (threshold 15). Drivers by points: if/else 9 (23 pts) (nesting depth added 14). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ImplicitMetadataOperation.updateMetadata (cognitive 23) · ×1

ImplicitMetadataOperation.updateMetadata (cognitive 23) spark/src/main/scala/org/apache/spark/sql/delta/schema/ImplicitMetadataOperation.scala:69 — ImplicitMetadataOperation.updateMetadata has cognitive complexity 23 (threshold 15). Drivers by points: if/else 11 (18 pts), boolean chains 5 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ParquetSchemaUtils.toParquetType (cognitive 23) · ×1

ParquetSchemaUtils.toParquetType (cognitive 23) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetSchemaUtils.java:302 — ParquetSchemaUtils.toParquetType has cognitive complexity 23 (threshold 15). Drivers by points: if/else 21 (22 pts), boolean chains 1 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · UnityCatalogTableOperations.doCommit (cognitive 23) · ×1

UnityCatalogTableOperations.doCommit (cognitive 23) icebergShaded/src/main/java/org/apache/iceberg/unityCatalog/UnityCatalogTableOperations.java:88 — UnityCatalogTableOperations.doCommit has cognitive complexity 23 (threshold 15). Drivers by points: if/else 11 (17 pts), boolean chains 4, loops 2 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaCommandPlugin.processCreateDeltaTable (cognitive 22) · ×1

DeltaCommandPlugin.processCreateDeltaTable (cognitive 22) spark-connect/server/src/main/scala/io/delta/connect/DeltaCommandPlugin.scala:117 — DeltaCommandPlugin.processCreateDeltaTable has cognitive complexity 22 (threshold 15). Drivers by points: if/else 13 (19 pts), loops 2, match/switch 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaHistoryManager.getEarliestRecreatableCommit (cognitive 22) · ×1

DeltaHistoryManager.getEarliestRecreatableCommit (cognitive 22) spark/src/main/scala/org/apache/spark/sql/delta/DeltaHistoryManager.scala:457 — DeltaHistoryManager.getEarliestRecreatableCommit has cognitive complexity 22 (threshold 15). Drivers by points: if/else 10 (20 pts), boolean chains 1, loops 1 (nesting depth added 10). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataFiltersBuilder.constructDataFilters (cognitive 22) · ×1

DataFiltersBuilder.constructDataFilters (cognitive 22) spark/src/main/scala/org/apache/spark/sql/delta/stats/DataFiltersBuilder.scala:241 — DataFiltersBuilder.constructDataFilters has cognitive complexity 22 (threshold 15). Drivers by points: if/else 10 (14 pts), boolean chains 7, match/switch 1 (nesting depth added 4). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · DataSkippingReaderBase.filesForScan (cognitive 22) · ×1

DataSkippingReaderBase.filesForScan (cognitive 22) spark/src/main/scala/org/apache/spark/sql/delta/stats/DataSkippingReader.scala:657 — DataSkippingReaderBase.filesForScan has cognitive complexity 22 (threshold 15). Drivers by points: if/else 12 (16 pts), boolean chains 5, match/switch 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ColumnDefaults.validateLiteral (cognitive 22) · ×1

ColumnDefaults.validateLiteral (cognitive 22) kernel/kernel-api/src/main/java/io/delta/kernel/internal/columndefaults/ColumnDefaults.java:133 — ColumnDefaults.validateLiteral has cognitive complexity 22 (threshold 15). Drivers by points: if/else 13 (14 pts), error handling 3 (6 pts), boolean chains 2 (nesting depth added 4). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · SuiteGeneratorConfig.applyCustomRulesAndGetAllMixins (cognitive 21) · ×1

SuiteGeneratorConfig.applyCustomRulesAndGetAllMixins (cognitive 21) spark/delta-suite-generator/src/main/scala/io/delta/suitegenerator/SuiteGeneratorConfig.scala:561 — SuiteGeneratorConfig.applyCustomRulesAndGetAllMixins has cognitive complexity 21 (threshold 15). Drivers by points: if/else 12 (21 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · CreateDeltaTableCommand.handleCreateTable (cognitive 21) · ×1

CreateDeltaTableCommand.handleCreateTable (cognitive 21) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:398 — CreateDeltaTableCommand.handleCreateTable has cognitive complexity 21 (threshold 15). Drivers by points: if/else 10 (14 pts), boolean chains 6, match/switch 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · AlterTableChangeColumnDeltaCommand.run (cognitive 21) · ×1

AlterTableChangeColumnDeltaCommand.run (cognitive 21) spark/src/main/scala/org/apache/spark/sql/delta/commands/alterDeltaTableCommands.scala:782 — AlterTableChangeColumnDeltaCommand.run has cognitive complexity 21 (threshold 15). Drivers by points: if/else 13 (17 pts), match/switch 2 (4 pts) (nesting depth added 6). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · BaseExternalLogStore.write (cognitive 21) · ×1

BaseExternalLogStore.write (cognitive 21) storage-s3-dynamodb/src/main/java/io/delta/storage/BaseExternalLogStore.java:168 — BaseExternalLogStore.write has cognitive complexity 21 (threshold 15). Drivers by points: if/else 9 (17 pts), boolean chains 2, error handling 2 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SnapshotManager.buildLogSegmentFromStartCheckpointVersion (cognitive 21) · ×1

SnapshotManager.buildLogSegmentFromStartCheckpointVersion (cognitive 21) kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/SnapshotManager.java:313 — SnapshotManager.buildLogSegmentFromStartCheckpointVersion has cognitive complexity 21 (threshold 15). Drivers by points: if/else 12 (15 pts), boolean chains 4, ternaries 2 (nesting depth added 3). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition.

D2 · Cognitive Complexity · DeltaSharingDataSource.sourceSchema (cognitive 20) · ×1

DeltaSharingDataSource.sourceSchema (cognitive 20) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingDataSource.scala:57 — DeltaSharingDataSource.sourceSchema has cognitive complexity 20 (threshold 15). Drivers by points: if/else 12 (17 pts), match/switch 1 (2 pts), boolean chains 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaSource.validateCommitAndDecideSkipping (cognitive 20) · ×1

DeltaSource.validateCommitAndDecideSkipping (cognitive 20) spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala:1030 — DeltaSource.validateCommitAndDecideSkipping has cognitive complexity 20 (threshold 15). Drivers by points: if/else 9 (14 pts), boolean chains 5, match/switch 1 (nesting depth added 5). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ParquetFilterUtils.convertComparatorToParquetFilter (cognitive 20) · ×1

ParquetFilterUtils.convertComparatorToParquetFilter (cognitive 20) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetFilterUtils.java:162 — ParquetFilterUtils.convertComparatorToParquetFilter has cognitive complexity 20 (threshold 15). Drivers by points: match/switch 6 (11 pts), if/else 6 (7 pts), boolean chains 2 (nesting depth added 6). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · Checkpointer.findLastCompleteCheckpointBeforeHelper (cognitive 20) · ×1

Checkpointer.findLastCompleteCheckpointBeforeHelper (cognitive 20) kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/Checkpointer.java:184 — Checkpointer.findLastCompleteCheckpointBeforeHelper has cognitive complexity 20 (threshold 15). Drivers by points: if/else 6 (13 pts), loops 2 (3 pts), boolean chains 2, error handling 1 (2 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaV2MicroBatchStream.applyPerCommitCDCAdmission (cognitive 20) · ×1

DeltaV2MicroBatchStream.applyPerCommitCDCAdmission (cognitive 20) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:2012 — DeltaV2MicroBatchStream.applyPerCommitCDCAdmission has cognitive complexity 20 (threshold 15). Drivers by points: if/else 10 (14 pts), boolean chains 3, loops 2 (3 pts) (nesting depth added 5). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaTableBuilder.addColumn (cognitive 20) · ×1

DeltaTableBuilder.addColumn (cognitive 20) python/delta/connect/tables.py:666 — DeltaTableBuilder.addColumn has cognitive complexity 20 (threshold 15). Drivers by points: if/else 14 (17 pts), boolean chains 3 (nesting depth added 3). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · OptimisticTransactionImpl.commitImpl (cognitive 19) · ×1

OptimisticTransactionImpl.commitImpl (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:1919 — OptimisticTransactionImpl.commitImpl has cognitive complexity 19 (threshold 15). Drivers by points: if/else 8, boolean chains 5, match/switch 3 (4 pts), error handling 2 (nesting depth added 1). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · AddFile.withoutTightBoundStatsPreservingPrecision (cognitive 19) · ×1

AddFile.withoutTightBoundStatsPreservingPrecision (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala:1120 — AddFile.withoutTightBoundStatsPreservingPrecision has cognitive complexity 19 (threshold 15). Drivers by points: if/else 7 (14 pts), loops 2 (4 pts), boolean chains 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · WriteIntoDeltaLike.getReplaceOnOrUsingExprOpt (cognitive 19) · ×1

WriteIntoDeltaLike.getReplaceOnOrUsingExprOpt (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/commands/WriteIntoDeltaLike.scala:386 — WriteIntoDeltaLike.getReplaceOnOrUsingExprOpt has cognitive complexity 19 (threshold 15). Drivers by points: if/else 9 (15 pts), boolean chains 3, match/switch 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SchemaMergingUtils.mergeDataTypes (cognitive 19) · ×1

SchemaMergingUtils.mergeDataTypes (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaMergingUtils.scala:193 — SchemaMergingUtils.mergeDataTypes has cognitive complexity 19 (threshold 15). Drivers by points: if/else 7 (10 pts), boolean chains 3, error handling 1 (3 pts), match/switch 2 (3 pts) (nesting depth added 6). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · PartitionUtils.parsePartitionValue (cognitive 19) · ×1

PartitionUtils.parsePartitionValue (cognitive 19) spark/src/main/scala/org/apache/spark/sql/delta/util/PartitionUtils.scala:906 — PartitionUtils.parsePartitionValue has cognitive complexity 19 (threshold 15). Drivers by points: if/else 8 (16 pts), match/switch 2 (3 pts) (nesting depth added 9). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · HadoopFileSystemLogStore.writeWithRename (cognitive 19) · ×1

HadoopFileSystemLogStore.writeWithRename (cognitive 19) storage/src/main/java/io/delta/storage/HadoopFileSystemLogStore.java:74 — HadoopFileSystemLogStore.writeWithRename has cognitive complexity 19 (threshold 15). Drivers by points: if/else 9 (13 pts), loops 2 (4 pts), error handling 1 (2 pts) (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · ParquetColumnWriters.createColumnWriter (cognitive 19) · ×1

ParquetColumnWriters.createColumnWriter (cognitive 19) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnWriters.java:94 — ParquetColumnWriters.createColumnWriter has cognitive complexity 19 (threshold 15). Drivers by points: if/else 17 (18 pts), boolean chains 1 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · MetadataCleanup.cleanupExpiredLogs (cognitive 19) · ×1

MetadataCleanup.cleanupExpiredLogs (cognitive 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/MetadataCleanup.java:83 — MetadataCleanup.cleanupExpiredLogs has cognitive complexity 19 (threshold 15). Drivers by points: if/else 7 (16 pts), boolean chains 2, loops 1 (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DataTypeJsonSerDe.fixupFieldLevelMetadata (cognitive 19) · ×1

DataTypeJsonSerDe.fixupFieldLevelMetadata (cognitive 19) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:275 — DataTypeJsonSerDe.fixupFieldLevelMetadata has cognitive complexity 19 (threshold 15). Drivers by points: if/else 5 (13 pts), ternaries 1 (3 pts), loops 1 (2 pts), boolean chains 1 (nesting depth added 11). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaV2MicroBatchStream.getCommitsFromRange (cognitive 19) · ×1

DeltaV2MicroBatchStream.getCommitsFromRange (cognitive 19) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1021 — DeltaV2MicroBatchStream.getCommitsFromRange has cognitive complexity 19 (threshold 15). Drivers by points: if/else 6 (11 pts), error handling 2 (4 pts), boolean chains 2, loops 1, ternaries 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · IcebergStatsUtils.icebergStatsToDelta (cognitive 18) · ×1

IcebergStatsUtils.icebergStatsToDelta (cognitive 18) iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergStatsUtils.scala:199 — IcebergStatsUtils.icebergStatsToDelta has cognitive complexity 18 (threshold 15). Drivers by points: if/else 5 (11 pts), boolean chains 3, match/switch 2 (3 pts), loops 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaColumnMappingBase.verifyAndUpdateMetadataChange (cognitive 18) · ×1

DeltaColumnMappingBase.verifyAndUpdateMetadataChange (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnMapping.scala:143 — DeltaColumnMappingBase.verifyAndUpdateMetadataChange has cognitive complexity 18 (threshold 15). Drivers by points: if/else 10 (13 pts), boolean chains 5 (nesting depth added 3). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · VacuumCommand.gc (cognitive 18) · ×1

VacuumCommand.gc (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/commands/VacuumCommand.scala:147 — VacuumCommand.gc has cognitive complexity 18 (threshold 15). Drivers by points: if/else 11, error handling 2 (3 pts), boolean chains 2, match/switch 2 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · CDCReaderBase.checkBatchCdfReadSchemaIncompatibility (cognitive 18) · ×1

CDCReaderBase.checkBatchCdfReadSchemaIncompatibility (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/commands/cdc/CDCReaderBase.scala:387 — CDCReaderBase.checkBatchCdfReadSchemaIncompatibility has cognitive complexity 18 (threshold 15). Drivers by points: if/else 7 (11 pts), boolean chains 7 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · RoaringBitmapArray.addRange (cognitive 18) · ×1

RoaringBitmapArray.addRange (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/deletionvectors/RoaringBitmapArray.scala:86 — RoaringBitmapArray.addRange has cognitive complexity 18 (threshold 15). Drivers by points: if/else 11 (15 pts), boolean chains 2, loops 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · TransactionalWrite.writeFiles (cognitive 18) · ×1

TransactionalWrite.writeFiles (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/files/TransactionalWrite.scala:406 — TransactionalWrite.writeFiles has cognitive complexity 18 (threshold 15). Drivers by points: if/else 9, boolean chains 4, match/switch 3, error handling 2. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · HadoopFileSystemLogStore.writeWithRename (cognitive 18) · ×1

HadoopFileSystemLogStore.writeWithRename (cognitive 18) spark/src/main/scala/org/apache/spark/sql/delta/storage/HadoopFileSystemLogStore.scala:120 — HadoopFileSystemLogStore.writeWithRename has cognitive complexity 18 (threshold 15). Drivers by points: if/else 10 (16 pts), error handling 1 (2 pts) (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UCDeltaTokenBasedRestClient.addMetadataUpdates (cognitive 18) · ×1

UCDeltaTokenBasedRestClient.addMetadataUpdates (cognitive 18) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:916 — UCDeltaTokenBasedRestClient.addMetadataUpdates has cognitive complexity 18 (threshold 15). Drivers by points: if/else 8 (14 pts), loops 2 (4 pts) (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UCDeltaTokenBasedRestClient.getCommits (cognitive 18) · ×1

UCDeltaTokenBasedRestClient.getCommits (cognitive 18) storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:301 — UCDeltaTokenBasedRestClient.getCommits has cognitive complexity 18 (threshold 15). Drivers by points: if/else 5 (10 pts), boolean chains 3, loops 1 (2 pts), ternaries 2, error handling 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · TableMetadata.reassignPartitionIds (cognitive 18) · ×1

TableMetadata.reassignPartitionIds (cognitive 18) icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:679 — TableMetadata.reassignPartitionIds has cognitive complexity 18 (threshold 15). Drivers by points: loops 4 (8 pts), if/else 4 (6 pts), ternaries 1 (4 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · SchemaUtils.convertKernelDataTypeToSparkDataType (cognitive 18) · ×1

SchemaUtils.convertKernelDataTypeToSparkDataType (cognitive 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:75 — SchemaUtils.convertKernelDataTypeToSparkDataType has cognitive complexity 18 (threshold 15). Drivers by points: if/else 18. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages. This shape REPEATS in the file: one other method here (SchemaUtils.convertSparkDataTypeToKernelDataType) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · SchemaUtils.convertSparkDataTypeToKernelDataType (cognitive 18) · ×1

SchemaUtils.convertSparkDataTypeToKernelDataType (cognitive 18) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/SchemaUtils.java:210 — SchemaUtils.convertSparkDataTypeToKernelDataType has cognitive complexity 18 (threshold 15). Drivers by points: if/else 18. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages. This shape REPEATS in the file: one other method here (SchemaUtils.convertKernelDataTypeToSparkDataType) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · Schema.stringToLiteral (cognitive 17) · ×1

Schema.stringToLiteral (cognitive 17) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:235 — Schema.stringToLiteral has cognitive complexity 17 (threshold 15). Drivers by points: if/else 8 (9 pts), boolean chains 5, error handling 2, match/switch 1 (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · Checkpoints.writeCheckpoint (cognitive 17) · ×1

Checkpoints.writeCheckpoint (cognitive 17) spark/src/main/scala/org/apache/spark/sql/delta/Checkpoints.scala:1070 — Checkpoints.writeCheckpoint has cognitive complexity 17 (threshold 15). Drivers by points: if/else 14, boolean chains 3. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · CreateDeltaTableCommand.replaceMetadataIfNecessary (cognitive 17) · ×1

CreateDeltaTableCommand.replaceMetadataIfNecessary (cognitive 17) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:847 — CreateDeltaTableCommand.replaceMetadataIfNecessary has cognitive complexity 17 (threshold 15). Drivers by points: if/else 7 (13 pts), boolean chains 4 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UpdateCommand.performUpdate (cognitive 17) · ×1

UpdateCommand.performUpdate (cognitive 17) spark/src/main/scala/org/apache/spark/sql/delta/commands/UpdateCommand.scala:114 — UpdateCommand.performUpdate has cognitive complexity 17 (threshold 15). Drivers by points: if/else 13 (15 pts), boolean chains 1, match/switch 1 (nesting depth added 2). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D2 · Cognitive Complexity · StatsCollector.collectStats (cognitive 17) · ×1

StatsCollector.collectStats (cognitive 17) spark/src/main/scala/org/apache/spark/sql/delta/stats/StatsCollectionUtils.scala:440 — StatsCollector.collectStats has cognitive complexity 17 (threshold 15). Drivers by points: if/else 6 (10 pts), error handling 2 (6 pts), match/switch 1 (nesting depth added 8). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · S3DynamoDBLogStore.tryEnsureTableExists (cognitive 17) · ×1

S3DynamoDBLogStore.tryEnsureTableExists (cognitive 17) storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:262 — S3DynamoDBLogStore.tryEnsureTableExists has cognitive complexity 17 (threshold 15). Drivers by points: error handling 3 (8 pts), if/else 5 (8 pts), loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DynamoDBCommitCoordinatorClient.tryEnsureTableExists (cognitive 17) · ×1

DynamoDBCommitCoordinatorClient.tryEnsureTableExists (cognitive 17) spark/src/main/java/io/delta/dynamodbcommitcoordinator/DynamoDBCommitCoordinatorClient.java:681 — DynamoDBCommitCoordinatorClient.tryEnsureTableExists has cognitive complexity 17 (threshold 15). Drivers by points: error handling 3 (8 pts), if/else 5 (8 pts), loops 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · UnityCatalogUtils.toUCTypeName (cognitive 17) · ×1

UnityCatalogUtils.toUCTypeName (cognitive 17) kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/UnityCatalogUtils.java:325 — UnityCatalogUtils.toUCTypeName has cognitive complexity 17 (threshold 15). Drivers by points: if/else 17. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · GeometryUtils.formatPointWKT (cognitive 17) · ×1

GeometryUtils.formatPointWKT (cognitive 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/GeometryUtils.java:39 — GeometryUtils.formatPointWKT has cognitive complexity 17 (threshold 15). Drivers by points: if/else 7 (11 pts), ternaries 2 (5 pts), boolean chains 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · VectorUtils.getValueAsObject (cognitive 17) · ×1

VectorUtils.getValueAsObject (cognitive 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/VectorUtils.java:138 — VectorUtils.getValueAsObject has cognitive complexity 17 (threshold 15). Drivers by points: if/else 15, boolean chains 2. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · DeltaHistoryManager.getActiveCommitAtTimestamp (cognitive 17) · ×1

DeltaHistoryManager.getActiveCommitAtTimestamp (cognitive 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/DeltaHistoryManager.java:164 — DeltaHistoryManager.getActiveCommitAtTimestamp has cognitive complexity 17 (threshold 15). Drivers by points: if/else 7 (8 pts), ternaries 2 (4 pts), error handling 1 (3 pts), boolean chains 2 (nesting depth added 5). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · TransactionImpl.commitWithRetry (cognitive 17) · ×1

TransactionImpl.commitWithRetry (cognitive 17) kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionImpl.java:397 — TransactionImpl.commitWithRetry has cognitive complexity 17 (threshold 15). Drivers by points: if/else 6 (12 pts), boolean chains 2, error handling 1 (2 pts), loops 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · StructField.collectNestedMapArrayTypeMetadata (cognitive 17) · ×1

StructField.collectNestedMapArrayTypeMetadata (cognitive 17) kernel/kernel-api/src/main/java/io/delta/kernel/types/StructField.java:273 — StructField.collectNestedMapArrayTypeMetadata has cognitive complexity 17 (threshold 15). Drivers by points: if/else 6 (13 pts), loops 2 (4 pts) (nesting depth added 9). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · KernelRowToSparkRow.equals (cognitive 17) · ×1

KernelRowToSparkRow.equals (cognitive 17) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:81 — KernelRowToSparkRow.equals has cognitive complexity 17 (threshold 15). Drivers by points: if/else 8 (15 pts), boolean chains 1, loops 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · KernelRowToSparkRow.toSparkValue (cognitive 17) · ×1

KernelRowToSparkRow.toSparkValue (cognitive 17) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:315 — KernelRowToSparkRow.toSparkValue has cognitive complexity 17 (threshold 15). Drivers by points: if/else 17. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · IdentityColumn.blockIdentityColumn (cognitive 16) · ×1

IdentityColumn.blockIdentityColumn (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/IdentityColumn.scala:464 — IdentityColumn.blockIdentityColumn has cognitive complexity 16 (threshold 15). Drivers by points: if/else 5 (14 pts), loops 1 (2 pts) (nesting depth added 10). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · OptimisticTransactionImpl.commitLarge (cognitive 16) · ×1

OptimisticTransactionImpl.commitLarge (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/OptimisticTransaction.scala:2158 — OptimisticTransactionImpl.commitLarge has cognitive complexity 16 (threshold 15). Drivers by points: match/switch 5 (8 pts), if/else 7, error handling 1 (nesting depth added 3). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · AbstractDeltaCatalog.loadTable (cognitive 16) · ×1

AbstractDeltaCatalog.loadTable (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:434 — AbstractDeltaCatalog.loadTable has cognitive complexity 16 (threshold 15). Drivers by points: if/else 8 (12 pts), error handling 2, boolean chains 1, match/switch 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · CreateDeltaTableCommand.assertTableSchemaDefined (cognitive 16) · ×1

CreateDeltaTableCommand.assertTableSchemaDefined (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:572 — CreateDeltaTableCommand.assertTableSchemaDefined has cognitive complexity 16 (threshold 15). Drivers by points: if/else 7 (15 pts), boolean chains 1 (nesting depth added 8). To reduce it, flatten the nesting: this score is depth rather than breadth — most of its points come from checks stacked inside one another, so the work sits several levels in. Invert each enclosing check into an early exit (a return, or the language's equivalent) so the happy path stays at one level, and where a level cannot be exited early, lift the block it encloses into its own named function.

D2 · Cognitive Complexity · MergeIntoCommandBase.validateNumRecords (cognitive 16) · ×1

MergeIntoCommandBase.validateNumRecords (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:574 — MergeIntoCommandBase.validateNumRecords has cognitive complexity 16 (threshold 15). Drivers by points: if/else 6 (13 pts), boolean chains 2, match/switch 1 (nesting depth added 7). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.

D2 · Cognitive Complexity · TruncateDeltaTableCommand.run (cognitive 16) · ×1

TruncateDeltaTableCommand.run (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/commands/TruncateDeltaTableCommand.scala:57 — TruncateDeltaTableCommand.run has cognitive complexity 16 (threshold 15). Drivers by points: if/else 5 (11 pts), loops 1 (3 pts), error handling 1, match/switch 1 (nesting depth added 8). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · CoordinatedCommitsUtils.commitFilesIterator (cognitive 16) · ×1

CoordinatedCommitsUtils.commitFilesIterator (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/coordinatedcommits/CoordinatedCommitsUtils.scala:582 — CoordinatedCommitsUtils.commitFilesIterator has cognitive complexity 16 (threshold 15). Drivers by points: if/else 7 (8 pts), match/switch 5 (7 pts), boolean chains 1 (nesting depth added 3). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · SchemaUtils.isReadCompatible (cognitive 16) · ×1

SchemaUtils.isReadCompatible (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/schema/SchemaUtils.scala:538 — SchemaUtils.isReadCompatible has cognitive complexity 16 (threshold 15). Drivers by points: boolean chains 8, if/else 5, match/switch 2 (3 pts) (nesting depth added 1). To reduce it, name the conditions: bind each compound test to a well-named local or a small predicate function, so the body reads as a sequence of named decisions rather than a chain of operators.

D2 · Cognitive Complexity · DeltaSourceBase.checkReadIncompatibleSchemaChanges (cognitive 16) · ×1

DeltaSourceBase.checkReadIncompatibleSchemaChanges (cognitive 16) spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala:578 — DeltaSourceBase.checkReadIncompatibleSchemaChanges has cognitive complexity 16 (threshold 15). Drivers by points: if/else 11 (15 pts), boolean chains 1 (nesting depth added 4). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · BitPacking.packBits2 (cognitive 16) · ×1

BitPacking.packBits2 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:215 — BitPacking.packBits2 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), if/else 2 (3 pts), loops 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · BitPacking.packBits3 (cognitive 16) · ×1

BitPacking.packBits3 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:271 — BitPacking.packBits3 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), loops 2 (3 pts), if/else 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: 4 other methods here (BitPacking.packBits4, BitPacking.packBits5, BitPacking.packBits6, …) have the same decision points, in the same order, at the same nesting depths — so this is one pattern written 5 times rather than 5 independent problems. Splitting this body alone leaves the other 4 exactly as they are. Where these are variations on one operation, the change that clears all 5 is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · BitPacking.packBits4 (cognitive 16) · ×1

BitPacking.packBits4 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:328 — BitPacking.packBits4 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), loops 2 (3 pts), if/else 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: 4 other methods here (BitPacking.packBits3, BitPacking.packBits5, BitPacking.packBits6, …) have the same decision points, in the same order, at the same nesting depths — so this is one pattern written 5 times rather than 5 independent problems. Splitting this body alone leaves the other 4 exactly as they are. Where these are variations on one operation, the change that clears all 5 is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · BitPacking.packBits5 (cognitive 16) · ×1

BitPacking.packBits5 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:386 — BitPacking.packBits5 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), loops 2 (3 pts), if/else 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: 4 other methods here (BitPacking.packBits3, BitPacking.packBits4, BitPacking.packBits6, …) have the same decision points, in the same order, at the same nesting depths — so this is one pattern written 5 times rather than 5 independent problems. Splitting this body alone leaves the other 4 exactly as they are. Where these are variations on one operation, the change that clears all 5 is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · BitPacking.packBits6 (cognitive 16) · ×1

BitPacking.packBits6 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:445 — BitPacking.packBits6 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), loops 2 (3 pts), if/else 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: 4 other methods here (BitPacking.packBits3, BitPacking.packBits4, BitPacking.packBits5, …) have the same decision points, in the same order, at the same nesting depths — so this is one pattern written 5 times rather than 5 independent problems. Splitting this body alone leaves the other 4 exactly as they are. Where these are variations on one operation, the change that clears all 5 is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · BitPacking.packBits7 (cognitive 16) · ×1

BitPacking.packBits7 (cognitive 16) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:505 — BitPacking.packBits7 has cognitive complexity 16 (threshold 15). Drivers by points: ternaries 6 (12 pts), loops 2 (3 pts), if/else 1 (nesting depth added 7). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body. This shape REPEATS in the file: 4 other methods here (BitPacking.packBits3, BitPacking.packBits4, BitPacking.packBits5, …) have the same decision points, in the same order, at the same nesting depths — so this is one pattern written 5 times rather than 5 independent problems. Splitting this body alone leaves the other 4 exactly as they are. Where these are variations on one operation, the change that clears all 5 is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.

D2 · Cognitive Complexity · ParquetColumnReaders.createConverter (cognitive 16) · ×1

ParquetColumnReaders.createConverter (cognitive 16) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:38 — ParquetColumnReaders.createConverter has cognitive complexity 16 (threshold 15). Drivers by points: if/else 14, boolean chains 2. To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · DataTypeJsonSerDe.nameToType (cognitive 16) · ×1

DataTypeJsonSerDe.nameToType (cognitive 16) kernel/kernel-api/src/main/java/io/delta/kernel/internal/types/DataTypeJsonSerDe.java:467 — DataTypeJsonSerDe.nameToType has cognitive complexity 16 (threshold 15). Drivers by points: if/else 11 (16 pts) (nesting depth added 5). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · TableMetadata.<init> (cognitive 16) · ×1

TableMetadata.<init> (cognitive 16) icebergShaded/src/main/java/org/apache/iceberg/TableMetadata.java:290 — TableMetadata.<init> has cognitive complexity 16 (threshold 15). Drivers by points: boolean chains 7, if/else 4 (6 pts), loops 2, ternaries 1 (nesting depth added 2). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · PartitionUtils.convertRowValueToKernelLiteral (cognitive 16) · ×1

PartitionUtils.convertRowValueToKernelLiteral (cognitive 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/PartitionUtils.java:338 — PartitionUtils.convertRowValueToKernelLiteral has cognitive complexity 16 (threshold 15). Drivers by points: if/else 15 (16 pts) (nesting depth added 1). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.

D2 · Cognitive Complexity · DeltaV2MicroBatchStream.checkReadIncompatibleSchemaChangeOnStreamStartOnce (cognitive 16) · ×1

DeltaV2MicroBatchStream.checkReadIncompatibleSchemaChangeOnStreamStartOnce (cognitive 16) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1542 — DeltaV2MicroBatchStream.checkReadIncompatibleSchemaChangeOnStreamStartOnce has cognitive complexity 16 (threshold 15). Drivers by points: if/else 6 (9 pts), loops 1 (4 pts), boolean chains 2, error handling 1 (nesting depth added 6). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.

D2 · Cognitive Complexity · DeltaTableBuilder.addColumn (cognitive 16) · ×1

DeltaTableBuilder.addColumn (cognitive 16) python/delta/tables.py:1393 — DeltaTableBuilder.addColumn has cognitive complexity 16 (threshold 15). Drivers by points: if/else 11 (14 pts), boolean chains 2 (nesting depth added 3). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.

D29 · Static Analysis (SAST) · REDACTED · ×1

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D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

D4 · Code Duplication · Near-duplicate member family (7 members, 16 shared lines) · ×1

Near-duplicate member family (7 members, 16 shared lines) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:164 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:164-200 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:216-256 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:272-313 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:329-371 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:387-430 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:446-490 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:506-551 — These 7 members are variants of one another: a block of 16 lines reported below appears in every one of them, and the pairwise near-duplicate rows they would otherwise produce are collapsed into this row. Read them as one construct written 7 times. The repair is at the members' grain — factor the shared implementation out once and have all of them call it with their differences as parameters or as an injected step, or, where the difference is systematic, generate them from one template. Extracting the individual blocks below is not the same fix: it leaves every body in place and the next edit still has to be made 7 times.

D4 · Code Duplication · Near-duplicate member family (4 members, 20 shared lines) · ×1

Near-duplicate member family (4 members, 20 shared lines) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:649 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:649-671 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:675-697 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:701-723 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:727-749 — These 4 members are variants of one another: a block of 20 lines reported below appears in every one of them, and the pairwise near-duplicate rows they would otherwise produce are collapsed into this row. Read them as one construct written 4 times. The repair is at the members' grain — factor the shared implementation out once and have all of them call it with their differences as parameters or as an injected step, or, where the difference is systematic, generate them from one template. Extracting the individual blocks below is not the same fix: it leaves every body in place and the next edit still has to be made 4 times.

D4 · Code Duplication · Near-duplicate member pair (39 shared lines) · ×1

Near-duplicate member pair (39 shared lines) iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:177 — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:177-227 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala:53-103 — These two members are variants of one another: 39 of their lines are already reported as duplicated blocks below, spread through both bodies rather than gathered into one. Read them as a single construct written twice. The repair is at the members' grain — factor the shared pipeline into one implementation the two call with their differences as parameters or as an injected step, or, where the difference is systematic (sync against async, one transport against another), generate one from the other. Extracting the individual blocks below is not the same fix: it leaves the two bodies in place and the next edit still has to be made twice.

D4 · Code Duplication · Edited copy of a member (23 corresponding lines) · ×1

Edited copy of a member (23 corresponding lines) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:597 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:597-619 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:623-645 — These two members are one piece of code written twice and then edited apart: 23 consecutive lines correspond almost exactly, broken only by small local edits. Most of that correspondence is NOT reported as duplicated blocks below — the edits cut it into fragments and only the largest of them clear the block floor, so the rows below understate it. The repair is at the members' grain — factor the shared implementation into one the two call with their differences as parameters or as an injected step, or, where the difference is systematic (an extra return value, one transport against another), generate one from the other. Left alone, the next edit has to be made twice and the two will drift further apart.

D4 · Code Duplication · Members sharing a duplicated core (8 members, 50+ identical tokens) · ×1

Members sharing a duplicated core (8 members, 50+ identical tokens) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:185 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:185-192 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:221-228 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:257-264 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:297-304 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:347-354 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:383-390 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:434-441 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:474-481 — These 8 members share a duplicated core: a run of at least 50 identical tokens appears in every one of them. That run is NOT broken out as duplicated-block rows below — it is what admitted this row, and the blocks below cover only the part of it that clears the block floor, so they understate the correspondence. Read the members as one construct written 8 times. The repair is at the members' grain — factor the shared implementation out once and have all of them call it with their differences as parameters or as an injected step, or, where the difference is systematic, generate them from one template. Extracting the individual blocks below is not the same fix: it leaves every body in place and the next edit still has to be made 8 times.

D4 · Code Duplication · Members sharing a duplicated core (7 members, 50+ identical tokens) · ×1

Members sharing a duplicated core (7 members, 50+ identical tokens) spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:138 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:138-159 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:172-195 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:197-224 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:231-261 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:269-302 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:311-348 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:358-398 — These 7 members share a duplicated core: a run of at least 50 identical tokens appears in every one of them. That run is NOT broken out as duplicated-block rows below — it is what admitted this row, and the blocks below cover only the part of it that clears the block floor, so they understate the correspondence. Read the members as one construct written 7 times. The repair is at the members' grain — factor the shared implementation out once and have all of them call it with their differences as parameters or as an injected step, or, where the difference is systematic, generate them from one template. Extracting the individual blocks below is not the same fix: it leaves every body in place and the next edit still has to be made 7 times.

D4 · Code Duplication · Members sharing a duplicated core (4 members, 50+ identical tokens) · ×1

Members sharing a duplicated core (4 members, 50+ identical tokens) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:203 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:203-212 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:259-268 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:316-325 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:374-383 — These 4 members share a duplicated core: a run of at least 50 identical tokens appears in every one of them. That run is NOT broken out as duplicated-block rows below — it is what admitted this row, and the blocks below cover only the part of it that clears the block floor, so they understate the correspondence. Read the members as one construct written 4 times. The repair is at the members' grain — factor the shared implementation out once and have all of them call it with their differences as parameters or as an injected step, or, where the difference is systematic, generate them from one template. Extracting the individual blocks below is not the same fix: it leaves every body in place and the next edit still has to be made 4 times.

D4 · Code Duplication · Duplicated block (20–21 lines × 2) · ×1

Duplicated block (20–21 lines × 2) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:371 — sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:371-391 | sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:496-515 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:371` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:515` calls `logInfo` and `sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingLogFileSystem.scala:391` does not — after which the two agree again for 4 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (20 lines × 2) · ×1

Duplicated block (20 lines × 2) sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingDataSource.scala:94 — sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingDataSource.scala:94-113 | sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingDataSource.scala:209-228 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `sharing/src/main/scala/io/delta/sharing/spark/DeltaSharingDataSource.scala:94` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (16–17 lines × 3) · ×1

Duplicated block (16–17 lines × 3) spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:519 — spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:519-534 | spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:598-614 | spark/src/main/scala/org/apache/spark/sql/delta/commands/UpdateCommand.scala:422-437 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from all 3 call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:519` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.

D4 · Code Duplication · Duplicated block (16 lines × 3) · ×1

Duplicated block (16 lines × 3) spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:587 — spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:587-602 | spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:733-748 | spark/src/main/scala/org/apache/spark/sql/delta/commands/UpdateCommand.scala:487-502 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from all 3 call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:587` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `spark/src/main/scala/org/apache/spark/sql/delta/commands/DeleteCommand.scala:585` calls `Map` and `spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala:732` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (13 lines × 3) · ×1

Duplicated block (13 lines × 3) REDACTED:3039 — REDACTED:3039-3051 | REDACTED:3060-3072 | REDACTED:3081-3093 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited.

D4 · Code Duplication · Duplicated block (7 lines × 4) · ×1

Duplicated block (7 lines × 4) spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:241 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:241-247 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:280-286 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:323-329 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:371-377 — all 4 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:241` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (3–7 lines × 4) · ×1

Duplicated block (3–7 lines × 4) spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:768 — spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:768-774 | spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:798-800 | spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:807-813 | spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:830-832 — all 4 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:768` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:813` calls `Try`, `getOrElse`, `Some` and `spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala:800` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (6 lines × 6) · ×1

Duplicated block (6 lines × 6) spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:190 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:190-195 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:219-224 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:256-261 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:297-302 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:343-348 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:393-398 — all 6 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:190` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:218` calls `result` and `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:189` does not — after which the two agree again for 3 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (6 lines × 3) · ×1

Duplicated block (6 lines × 3) spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:381 — spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:381-386 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:405-410 | spark/src/main/scala/org/apache/spark/sql/delta/DeltaImplicitCast.scala:103-108 — there are 3 copies across 2 file(s) — more copies than files, so at least one file holds the block twice. Extract it once into a single shared function every call site can reach and call it from all 3 sites; resolving a subset leaves the remainder to drift apart. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:381` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `spark/src/main/scala/org/apache/spark/sql/delta/DeltaImplicitCast.scala:109` calls `withNewQuery` and `spark/src/main/scala/org/apache/spark/sql/delta/DeltaAnalysis.scala:387` does not — after which the two agree again for 3 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (5 lines × 7) · ×1

Duplicated block (5 lines × 7) spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:139 — spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:139-143 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:173-177 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:198-202 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:232-236 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:270-274 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:312-316 | spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:359-363 — all 7 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:139` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (32 lines × 2) · ×1

Duplicated block (32 lines × 2) spark/src/main/scala-shims/spark-4.0/DataSourceV2RelationShims.scala:39 — spark/src/main/scala-shims/spark-4.0/DataSourceV2RelationShims.scala:39-70 | spark/src/main/scala-shims/spark-4.1-4.3/DataSourceV2RelationShims.scala:39-70 — `spark/src/main/scala-shims/spark-4.0/DataSourceV2RelationShims.scala` and `spark/src/main/scala-shims/spark-4.1-4.3/DataSourceV2RelationShims.scala` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 1 separate duplicated blocks between them, totalling at least 32 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala-shims/spark-4.0/DataSourceV2RelationShims.scala:39` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.

D4 · Code Duplication · Duplicated block (27 lines × 3) · ×1

Duplicated block (27 lines × 3) spark/src/main/scala-shims/spark-4.0/RelocatedStreamingClassesShims.scala:54 — spark/src/main/scala-shims/spark-4.0/RelocatedStreamingClassesShims.scala:54-80 | spark/src/main/scala-shims/spark-4.1/RelocatedStreamingClassesShims.scala:57-83 | spark/src/main/scala-shims/spark-4.2-4.3/RelocatedStreamingClassesShims.scala:57-108 — `spark/src/main/scala-shims/spark-4.0/RelocatedStreamingClassesShims.scala` and `spark/src/main/scala-shims/spark-4.1/RelocatedStreamingClassesShims.scala` are one unit implemented once per sibling directory, so they are most likely parallel implementations of one contract rather than a copy of each other — this scan matched 1 separate duplicated blocks between them, totalling at least 52 lines. If both are selected at run time, neither can be retired in favour of the other, and the lines that DIFFER between them are the reason both exist. The move that pays here is to hoist the identical part into a shared location the whole family can reach and give what differs a parameter or a seam, so a change lands once instead of once per sibling; extracting one helper per block leaves every sibling to drift on its own. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/scala-shims/spark-4.0/RelocatedStreamingClassesShims.scala:54` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.

D4 · Code Duplication · Duplicated block (58 lines × 2) · ×1

Duplicated block (58 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:164 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:164-221 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:238-295 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/KernelRowToSparkRow.java:164` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (19 lines × 2) · ×1

Duplicated block (19 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:485 — kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:485-503 | kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:549-567 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/statistics/DataFileStatistics.java:485` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (12–14 lines × 2) · ×1

Duplicated block (12–14 lines × 2) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1319 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1319-1330 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1852-1865 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:1319` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (12–13 lines × 2) · ×1

Duplicated block (12–13 lines × 2) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:205 — icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:205-217 | icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:238-249 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:205` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (10 lines × 3) · ×1

Duplicated block (10 lines × 3) icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:580 — icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:580-591 | icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:709-718 | icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:735-744 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `icebergShaded/src/main/java/org/apache/iceberg/hive/HiveCatalog.java:580` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (8–9 lines × 2) · ×1

Duplicated block (8–9 lines × 2) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:174 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:174-182 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:205-212 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/json/JsonUtils.java:174` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (8 lines × 6) · ×1

Duplicated block (8 lines × 6) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:612 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:612-619 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:638-645 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:664-671 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:690-697 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:716-723 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:742-749 — all 6 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:612` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on.

D4 · Code Duplication · Duplicated block (6–7 lines × 2) · ×1

Duplicated block (6–7 lines × 2) kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:179 — kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:179-185 | kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:205-210 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/DataSkippingUtils.java:179` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.

D4 · Code Duplication · Duplicated block (6 lines × 10) · ×1

Duplicated block (6 lines × 10) spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:598 — spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:598-603 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:610-615 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:622-627 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:656-661 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:668-673 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:681-686 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:693-698 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:705-710 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:717-722 | spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:729-734 — all 10 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/v2/src/main/java/org/apache/spark/sql/delta/v2/utils/ExpressionUtils.java:598` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (6 lines × 8) · ×1

Duplicated block (6 lines × 8) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:187 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:187-192 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:223-228 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:259-264 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:299-304 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:349-354 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:385-390 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:436-441 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:476-481 — all 8 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java:187` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (5 lines × 3) · ×1

Duplicated block (5 lines × 3) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:438 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:438-442 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:498-502 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:559-563 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:438` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (57 lines × 2) · ×1

Duplicated block (57 lines × 2) spark/src/main/java/io/delta/dynamodbcommitcoordinator/ReflectionUtils.java:1 — spark/src/main/java/io/delta/dynamodbcommitcoordinator/ReflectionUtils.java:1-62 | storage-s3-dynamodb/src/main/java/io/delta/storage/utils/ReflectionUtils.java:1-57 — the copies span different directories, so extracting a shared function means choosing where it lives: put it somewhere both call sites can already reach — a location they all depend on today, or a new shared one if there is none — and call it from each site; until then, every change has to be made twice. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/io/delta/dynamodbcommitcoordinator/ReflectionUtils.java:1` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (9 lines × 5) · ×1

Duplicated block (9 lines × 5) kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultBooleanVector.java:36 — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultBooleanVector.java:36-44 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultByteVector.java:36-44 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultDoubleVector.java:36-44 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultFloatVector.java:36-44 | kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultShortVector.java:36-44 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from all 5 call sites, so a change lands once. Note first that the copies are not typed on the same thing: the declarations holding them bind `values` to `boolean[]` in one and `byte[]` in another, and the duplicated lines use it. The extracted unit therefore needs a parameter type that fits BOTH — their common supertype where they have one, or a new abstraction over them where they do not — and settling that is the step that comes BEFORE the extraction above. Where the two types are deliberately unrelated, the duplication is the price of that separation and the honest resolution is to record the decision rather than to extract.

D4 · Code Duplication · Duplicated block (8 lines × 4) · ×1

Duplicated block (8 lines × 4) spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:650 — spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:650-657 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:676-683 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:702-709 | spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:728-735 — all 4 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java:650` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.

D4 · Code Duplication · Duplicated block (19–20 lines × 3) · ×1

Duplicated block (19–20 lines × 3) python/delta/tables.py:1524 — python/delta/tables.py:1524-1543 | python/delta/tables.py:1567-1586 | python/delta/tables.py:1666-1684 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.

D4 · Code Duplication · Duplicated block (39 lines × 2) · ×1

Duplicated block (39 lines × 2) examples/scala/src/main/scala/example/QuickstartSQL.scala:41 — examples/scala/src/main/scala/example/QuickstartSQL.scala:41-79 | examples/scala/src/main/scala/example/QuickstartSQLOnPaths.scala:41-79 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `examples/scala/src/main/scala/example/QuickstartSQL.scala:41` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `examples/scala/src/main/scala/example/QuickstartSQL.scala:83` calls `sql`, `show` and `examples/scala/src/main/scala/example/QuickstartSQLOnPaths.scala:80` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (57–58 lines × 3) · ×1

Duplicated block (57–58 lines × 3) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:96 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:96-153 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:272-329 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:351-407 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:96` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. The `return` at the foot of the matched lines is the enclosing body's own terminal exit, not an early one: it moves with them unchanged, and each site calls the extracted unit from the position that `return` occupied — no decision has to be handed back and re-acted on. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:93` calls `withSchema` and `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/CreateTableAndInsertData.java:269` does not — after which the two agree again for 4 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

D4 · Code Duplication · Duplicated block (23 lines × 2) · ×1

Duplicated block (23 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:56 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:56-78 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:97-119 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/integration/ReadIntegrationTestSuite.java:56` it runs out through the closing brace of the declaration holding it and carries on into the declaration that follows — the window is the tail of one member plus the head of the next, so no call can be substituted for those exact lines, and the smallest declaration that contains all of them is the type they sit in. The repeated unit is the member each site sits in: where those members' bodies are the same, move one whole member to the shared location and have the others delegate to it; where the copies are a run of near-identical overloads or wrappers that differ only in their signatures, the repetition IS the run — a one-line delegation has no helper inside it to lift — so generate the run from the set it enumerates, or accept it and keep each member's own documentation with it.

D4 · Code Duplication · Duplicated block (13–14 lines × 2) · ×1

Duplicated block (13–14 lines × 2) kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:243 — kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:243-256 | kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/SingleThreadedTableReader.java:114-126 — the copies sit in sibling files of one directory, so a shared home is within easy reach: extract the block into a single shared function the call sites can all reach — a file they already depend on, or a new one alongside them — and call it from both call sites, so a change lands once. Read the line range as the matched WINDOW rather than a finished unit: at `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:243` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/MultiThreadedTableReader.java:241` calls `getPhysicalDataReadSchema` and `kernel/examples/kernel-examples/src/main/java/io/delta/kernel/examples/SingleThreadedTableReader.java:113` does not — after which the two agree again for 2 more lines. One of those two behaviours is the intended one and the other is what a copy-paste left behind, so decide which BEFORE unifying them: extracting the shared part will silently settle it, and if the copy that skips the call is the wrong one, that bug is already live.

M1 · Documentation (README) · README may be stale · ×1

README may be stale — 538 code files changed in the last 6 months but the README was not touched — it may no longer reflect the system.

P12 · CI test-gate honesty · Coverage collected but not gated · ×1

Coverage collected but not gated — CI collects a coverage report but no step enforces a minimum — coverage could halve and CI stays green. Add a step that fails the build when coverage drops below a floor (your coverage tool's minimum-threshold flag, or a coverage-gate action) so the number guards something. What was searched, so you can tell an absence from a miss: this repository's CI files AND its coverage configuration — the well-known coverage and test-runner config files, read at the repository root and inside workspace package directories two levels down, so a floor declared beside the tests rather than in the pipeline is credited — matched against the threshold settings this check knows by name. A floor set in your coverage service's web UI rather than in a committed file, or under a setting whose name is not one of those, is not seen here.

S1 · Web-Security Posture · Weak hash algorithm · ×1

Weak hash algorithm spark/src/main/scala/org/apache/spark/sql/delta/LastCheckpointInfo.scala:286 — MD5/SHA1 is computed here, and both are collision-broken. If this digest protects anything — a signature, an integrity or tamper check, a credential, or any value an attacker can influence — that is a real weakness: use SHA-256+ (`MessageDigest.getInstance("SHA-256")`) for content integrity, or a KDF (bcrypt/Argon2/scrypt) for password storage. If it only derives a non-security identifier (a cache key, an avatar URL, an ETag), collision resistance carries no security consequence here; make that intent explicit instead — a non-cryptographic hash such as xxhash or murmurhash says it in code — since the algorithm alone cannot distinguish the two uses. Where a protocol this code does not own fixes the digest (a k-anonymity range query, a legacy signature format), the protocol decides; say so beside the call.

X17 · Uncapped recursion over a caller-supplied document · Recursive walk over a caller-supplied document has no depth cap · ×1

Recursive walk over a caller-supplied document has no depth cap spark/src/main/scala/org/apache/spark/sql/delta/LastCheckpointInfo.scala:264 — `LastCheckpointInfo.treeNodeToChecksum` is public, takes a document from its caller (line 256) and hands it to `traverseJsonNode`, which calls itself at line 264 with a piece of `currentNode` (and at line 270), not as a tail call the compiler turns into a loop — and nowhere in `traverseJsonNode` is there a depth parameter, a descent counter, or any other cap. The walk therefore spends one stack frame per LEVEL of the value it is handed, so the nesting of the caller's document — not this code — decides how deep the stack goes. On the JVM's default 1 MB thread stack a walk like this one throws `StackOverflowError` from about 500–2,000 levels on a cold first call and 6,000–17,000 once warmed up (OpenJDK 21 and 25), while `ujson.read`, Jackson's `readTree` before 2.15 and circe before 0.14.16 accept any nesting (2,000,000 levels from 4 MB) and circe 0.14.16 accepts 4,096 — on a cold JVM even play-json's cap of 1,000 is past the point the walk fails. `StackOverflowError` is not `NonFatal`: `Try`, `case NonFatal(e)` and `recover` do not stop it, and in a `Future` on the global execution context it leaves the future forever incomplete. Thread a depth argument through `traverseJsonNode` and reject the value past a fixed maximum, or rewrite the descent with an explicit stack.

X18 · Disposal-pattern correctness · Disposable created and abandoned in the function that made it · ×1

Disposable created and abandoned in the function that made it spark/delta-suite-generator/src/main/scala/io/delta/suitegenerator/SuitesWriter.scala:123 — `Files.walk(…)` opens something that has to be given back — a file descriptor, a socket, a directory handle — and its only use reads `.iterator` through it and drops it, so this expression both creates the value and is the last place that can release it, and does not. Every call leaks one more open handle until the collector happens to reach it: `Too many open files` under load, and on Windows a file that cannot be replaced or deleted while it is held. Open it with `scala.util.Using.resource(Files.walk(…)) { r => … }`, which releases it on every path including a throw, or hold it and call `.close()` in a `finally`.

Minor — 251 finding(s)

D34 · Knowledge Freshness · Orphaned file · ×180

Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/skipping/clustering/ClusteredTableUtils.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file hudi/src/main/scala/org/apache/spark/sql/delta/hudi/HudiConversionTransaction.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PaginatedScanFilesIteratorImpl.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/stats/AutoCompactPartitionStats.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/rowtracking/RowTracking.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/perf/DeltaOptimizedWriterExec.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/commitrange/CommitRangeFactory.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/commands/OptimizeTableStrategy.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceOffset.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/io/delta/tables/DeltaTableBuilder.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/commands/optimize/OptimizeStats.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaTableBuilder.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/commit/CommitMetadata.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/tablefeatures/TableFeature.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/snapshot/MetadataCleanup.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/storage/dv/DeletionVectorStore.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/CommitRangeBuilder.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/DeltaTableValueFunctions.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/PreprocessTableWithDVs.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/table/SnapshotBuilderImpl.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file spark/src/main/scala/org/apache/spark/sql/delta/stats/DataSkippingStatsTracker.scala:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
Orphaned file kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/ProtocolMetadataLogReplay.java:1 — No one still active in this repository holds living knowledge of this file: everyone who made a meaningful change to it has gone quiet, or what the current team did to it (moves, reformatting, log-level or import edits, renames) never needed understanding it. If it breaks, no one currently understands it. Attach the read to the next change that touches it: have a second person review that change, and leave behind a short comment or test recording what the file is for.
+ 155 more in this group — see findings.md.

X10 · Duplicated predicate · Duplicated predicate · ×25

Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionMetadataFactory.java:406 — `!readVersionSupportsCatalogManaged && writeVersionSupportsCatalogManaged` appears character-identically in 2 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionMetadataFactory.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/DirectoryCreationUtils.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/types/ArrayType.java:75 — `dataType == null || getClass() != dataType.getClass()` appears character-identically in 3 files — kernel/kernel-api/src/main/java/io/delta/kernel/types/ArrayType.java, kernel/kernel-api/src/main/java/io/delta/kernel/types/MapType.java, kernel/kernel-api/src/main/java/io/delta/kernel/types/StructType.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/expressions/Literal.java:214 — `dataType instanceof GeometryType || dataType instanceof GeographyType` appears character-identically in 4 files — kernel/kernel-api/src/main/java/io/delta/kernel/expressions/Literal.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/JsonUtils.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultJsonRow.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetStatsReader.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/VectorUtils.java:147 — `dataType instanceof IntegerType || dataType instanceof DateType` appears character-identically in 4 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/util/VectorUtils.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultIntVector.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultLongVector.java:41 — `dataType instanceof LongType || dataType instanceof TimestampType || dataType instanceof TimestampNTZType` appears character-identically in 3 files — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/vector/DefaultLongVector.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnReaders.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/StatsSchemaHelper.java:224 — `dataType instanceof TimestampType || dataType instanceof TimestampNTZType` appears character-identically in 3 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/skipping/StatsSchemaHelper.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetColumnWriters.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/TimestampConverters.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionBuilderImpl.java:329 — `lastTxnVersion.isPresent() && lastTxnVersion.get() >= txnId.getVersion()` appears character-identically in 2 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/TransactionBuilderImpl.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/UpdateTableTransactionBuilderImpl.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java:70 — `left.isNullAt(rowId) || right.isNullAt(rowId)` appears character-identically in 3 files — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/DefaultExpressionUtils.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/LikeExpressionEvaluator.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/expressions/StartsWithExpressionEvaluator.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/files/LogDataUtils.java:34 — `logData instanceof ParsedCatalogCommitData && logData.isFile()` appears character-identically in 2 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/files/LogDataUtils.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/table/SnapshotFactory.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/DomainMetadata.java:160 — `obj == null || getClass() != obj.getClass()` appears character-identically in 4 files — kernel/kernel-api/src/main/java/io/delta/kernel/internal/actions/DomainMetadata.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PageToken.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/rowtracking/RowTrackingMetadataDomain.java, storage/src/main/java/io/delta/storage/commit/Commit.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultColumnarBatch.java:77 — `ordinal < 0 || ordinal >= columnVectors.size()` appears character-identically in 2 files — kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultColumnarBatch.java, kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/data/DefaultRowBasedColumnarBatch.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/adapters/UniformAdapter.java:60 — `properties == null || properties.isEmpty()` appears character-identically in 2 files — kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/adapters/UniformAdapter.java, spark/src/main/java/org/apache/spark/sql/delta/util/CatalogTableUtils.java. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate python/delta/connect/tables.py:682 — `generatedAlwaysAs is not None and generatedByDefaultAs is not None` appears character-identically in 2 files — python/delta/connect/tables.py, python/delta/tables.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate python/delta/connect/tables.py:766 — `len(cols) == 1 and isinstance(cols[0], (list, tuple))` appears character-identically in 2 files — python/delta/connect/tables.py, python/delta/tables.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate python/delta/connect/tables.py:677 — `type(dataType) is not str and not isinstance(dataType, DataType)` appears character-identically in 2 files — python/delta/connect/tables.py, python/delta/tables.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate python/delta/connect/tables.py:804 — `type(key) is not str or type(value) is not str` appears character-identically in 2 files — python/delta/connect/tables.py, python/delta/tables.py. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala/org/apache/spark/sql/delta/IdentityColumn.scala:324 — `ColumnWithDefaultExprUtils.isIdentityColumn(f) && !IdentityColumn.allowExplicitInsert(f)` appears character-identically in 2 files — spark/src/main/scala/org/apache/spark/sql/delta/IdentityColumn.scala, spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommandBase.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala:611 — `a.baseRowId.nonEmpty || a.defaultRowCommitVersion.nonEmpty` appears character-identically in 2 files — spark/src/main/scala/org/apache/spark/sql/delta/ConflictChecker.scala, spark/src/main/scala/org/apache/spark/sql/delta/commands/backfill/RowTrackingUnBackfillExecutor.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala-shims/spark-4.2/PropagateSchemaEvolutionWriteOptionShims.scala:31 — `a.withSchemaEvolution && !a.writeOptions.contains(DeltaOptions.MERGE_SCHEMA_OPTION)` appears character-identically in 2 files — spark/src/main/scala-shims/spark-4.2/PropagateSchemaEvolutionWriteOptionShims.scala, spark/src/main/scala-shims/spark-4.3/PropagateSchemaEvolutionWriteOptionShims.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaColumnBuilder.scala:193 — `dataType != null && dataType != LongType` appears character-identically in 2 files — spark-connect/client/src/main/scala/io/delta/connect/tables/DeltaColumnBuilder.scala, spark/src/main/scala/io/delta/tables/DeltaColumnBuilder.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala:281 — `endOffset.index >= 0 && (startVersion < endOffset.reservoirVersion || startIndex < endOffset.index)` appears character-identically in 2 files — spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSource.scala, spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceCDCSupport.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala:1510 — `fs.exists(path) && fs.listStatus(path).nonEmpty` appears character-identically in 2 files — spark/src/main/scala/org/apache/spark/sql/delta/catalog/AbstractDeltaCatalog.scala, spark/src/main/scala/org/apache/spark/sql/delta/commands/CreateDeltaTableCommand.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:237 — `input.length > 1 && ((input.head == '\'' && input.last == '\'') || (input.head == '"' && input.last == '"'))` appears character-identically in 2 files — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala, spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala:246 — `input.startsWith("x") || input.startsWith("X")` appears character-identically in 2 files — iceberg/src/main/scala/org/apache/spark/sql/delta/icebergShaded/DeltaToIcebergConvert.scala, spark/src/main/scala/org/apache/spark/sql/delta/DeltaColumnDefaults.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.
Duplicated predicate spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommand.scala:128 — `isInsertOnly && spark.conf.get(DeltaSQLConf.MERGE_INSERT_ONLY_ENABLED)` appears character-identically in 2 files — spark/src/main/scala/org/apache/spark/sql/delta/commands/MergeIntoCommand.scala, spark/src/main/scala/org/apache/spark/sql/delta/commands/merge/MergeIntoMaterializeSource.scala. It is one line, so the duplication detector's token window never sees it; the copies drift when only one is corrected. Give the condition a name and one home.

IC1 · Incompleteness & stubs · Blanket warning suppression · ×8

Blanket warning suppression iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergFileManifest.scala:200 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression iceberg/src/main/scala/org/apache/spark/sql/delta/IcebergSchemaUtils.scala:47 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression spark/src/main/scala/org/apache/spark/sql/delta/AllowedUserProvidedExpressions.scala:41 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression REDACTED:202 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression spark/src/main/scala/org/apache/spark/sql/delta/DeltaOptions.scala:66 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression spark/src/main/scala/org/apache/spark/sql/delta/PreDowngradeTableFeatureCommand.scala:245 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala:1011 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.
Blanket warning suppression spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceMetadataEvolutionSupport.scala:849 — A bare `// scalastyle:off`, `// scalafix:off` or `@nowarn` (or Wartremover's `warts.All`) switches every rule or warning off — hidden debt. Suppress the specific rule on the specific line, with a justification, instead.

X4 · Structured logging · Interpolated log message defeats structured logging · ×8

Interpolated log message defeats structured logging storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java:170 — `debug` at line 170 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.debug("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:366 — `info` at line 366 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:387 — `warn` at line 387 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.warn("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:519 — `info` at line 519 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:602 — `info` at line 602 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCCommitCoordinatorClient.java:624 — `warn` at line 624 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.warn("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging spark/v2/src/main/java/org/apache/spark/sql/delta/v2/read/DeltaV2MicroBatchStream.java:355 — `info` at line 355 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.
Interpolated log message defeats structured logging kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ParquetBatchRowReader.java:197 — `info` at line 197 is handed a message assembled at the call — a string concatenated with a value, or `String.format` — through SLF4J or log4j 2, so the logger receives one finished string: the values in it cannot be queried, filtered or aggregated as fields, every occurrence reads as a different message, and the string is built even when the level is filtered out. Pass a constant pattern and the values beside it instead: `log.info("Order {} moved to {}", orderId, status)`, which keeps the pattern and its arguments apart on the event for a structured encoder (logstash-logback-encoder, log4j 2's JsonTemplateLayout, OpenTelemetry), or `log.atInfo().addKeyValue("order_id", orderId).log("order moved")` with SLF4J 2's fluent API. An exception goes last, as the throwable argument, not into the text.

D16 · Bus Factor · Off-boarding risk · ×7

Off-boarding risk: anonymized user #1 — If anonymized user #1 becomes unavailable, 14 significant file(s) lose their only recent owner: flink/src/main/java/io/delta/flink/sink/DeltaSinkConf.java, flink/src/main/java/io/delta/flink/sink/DeltaWriterTask.java, flink/src/main/java/io/delta/flink/sink/DeltaCommitter.java, flink/src/main/java/io/delta/flink/sink/mergestrategy/CoWUpsert.java, flink/src/main/java/io/delta/flink/sink/mergestrategy/MoRUpsert.java, flink/src/main/java/io/delta/flink/kernel/dv/RoaringBitmapArray.java, flink/src/main/java/io/delta/flink/kernel/dv/BinDVAccess.java, flink/src/main/java/io/delta/flink/table/DeltaTable.java (+6 more). Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #2 — If anonymized user #2 becomes unavailable, 4 significant file(s) lose their only recent owner: spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/BitPacking.java, spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/PFOREncoding.java, spark/src/main/java/org/apache/spark/sql/delta/deletionvectors/mumbling/MumblingBitmap.java, spark/src/main/scala/org/apache/spark/sql/delta/ContiguousVersionIterator.scala. Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #3 — If anonymized user #3 becomes unavailable, 4 significant file(s) lose their only recent owner: iceberg/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/SparkToIcebergExpressionConverter.scala, spark/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/ServerSidePlanningClient.scala, spark/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/UnityCatalogMetadata.scala, spark/src/main/scala/org/apache/spark/sql/delta/serverSidePlanning/ServerSidePlanningMetadata.scala. Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #4 — If anonymized user #4 becomes unavailable, 3 significant file(s) lose their only recent owner: spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaStreamUtils.scala, spark/src/main/scala/org/apache/spark/sql/delta/files/DeltaSourceSnapshot.scala, kernel/kernel-api/src/main/java/io/delta/kernel/exceptions/StartVersionNotFoundException.java. Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #5 — If anonymized user #5 becomes unavailable, 3 significant file(s) lose their only recent owner: kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PaginatedScanFilesIteratorImpl.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PageToken.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PaginationContext.java. Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #6 — If anonymized user #6 becomes unavailable, 3 significant file(s) lose their only recent owner: kernel/kernel-api/src/main/java/io/delta/kernel/internal/commitrange/CommitRangeFactory.java, kernel/kernel-api/src/main/java/io/delta/kernel/CommitRangeBuilder.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/commitrange/CommitRangeBuilderImpl.java. Pair on, review, or document these before any departure.
Off-boarding risk: anonymized user #7 — If anonymized user #7 becomes unavailable, 3 significant file(s) lose their only recent owner: kernel/kernel-api/src/main/java/io/delta/kernel/commit/CommitMetadata.java, kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/metrics/UcPublishTelemetry.java, kernel/unitycatalog/src/main/java/io/delta/kernel/unitycatalog/metrics/UcCommitTelemetry.java. Pair on, review, or document these before any departure.

IC1 · Incompleteness & stubs · Disabled test · ×7

Disabled test kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/DeltaIcebergCompatV2Suite.scala:52 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/DeltaIcebergCompatV2Suite.scala:58 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/IcebergWriterCompatV1Suite.scala:765 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/LogReplaySuite.scala:247 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test kernel/kernel-defaults/src/test/scala/io/delta/kernel/defaults/LogReplaySuite.scala:256 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test spark/src/test/scala/org/apache/spark/sql/delta/IdentityColumnSuite.scala:453 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.
Disabled test spark/src/test/scala/org/apache/spark/sql/delta/MergeIntoSuiteBase.scala:2726 — A test is skipped/ignored — coverage that looks present but never runs. Re-enable it or delete it so the green run means something.

X7 · Silent fallback defaults · Silent fallback default on parse failure · ×2

Silent fallback default on parse failure storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:211 — `fetchStagingCredentials` returns `Collections.emptyMap()` when `IllegalArgumentException | NullPointerException` is thrown, with no log or throw — a malformed value silently becomes that default. Log the input or fail validation. If that constant is the correct answer rather than a stand-in for a value that could not be read, say so in a comment in the catch or in the Javadoc, and the row stops firing.
Silent fallback default on parse failure storage/src/main/java/io/delta/storage/commit/uccommitcoordinator/UCDeltaTokenBasedRestClient.java:196 — `fetchTableCredentials` returns `Collections.emptyMap()` when `IllegalArgumentException` is thrown, with no log or throw — a malformed value silently becomes that default. Log the input or fail validation. If that constant is the correct answer rather than a stand-in for a value that could not be read, say so in a comment in the catch or in the Javadoc, and the row stops firing.

D16 · Bus Factor · Further sole-owners (lower concentration) · ×1

Further sole-owners (lower concentration) — 26 other contributor(s) are each the sole owner of a small amount of code below the off-boarding threshold — folded into the bus-factor score and metrics (68 single-owned of 792 analysed files in total, counted over production source files of roughly 2,400 bytes or more, excluding vendored, generated, example/demo and scaffolding-template trees and test files identified by path convention, largest first; 792 of the 1126 production source files in this repository met that bar). They are anonymized user #8 (3 file(s)), anonymized user #9 (2 file(s)), anonymized user #10 (2 file(s)), anonymized user #11 (2 file(s)), anonymized user #12 (2 file(s)), anonymized user #13 (2 file(s)) (+20 more) — spread or document their files in the same way, at lower priority than the named off-boarding risks above. The files folded here: kernel/kernel-api/src/main/java/io/delta/kernel/internal/data/GenericColumnVector.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/LogReplayUtils.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/checkpoints/LastCheckpointFileReader.java, spark/src/main/scala/org/apache/spark/sql/delta/hooks/AutoCompactUtils.scala, spark/src/main/scala/org/apache/spark/sql/delta/amt/AMTPartitionValues.scala, spark/v2/src/main/scala/org/apache/spark/sql/delta/v2/tablemanager/CachedSnapshotManager.scala, spark/src/main/scala/org/apache/spark/sql/delta/util/DeltaFileSystemOptions.scala, flink/src/main/java/io/delta/flink/sink/sql/FlinkUnityCatalogTable.java (+26 more).

D26 · Project Cohesion · Projects may be oversized for their cohesion · ×1

Projects may be oversized for their cohesion — 1 of 3 project(s) overshoot their size bounds, lowering Project Cohesion to 3.3/10. The most over is `(repository root)` (233828 LoC, 2429 module-visible types across 201 directories). Review these for cohesion — draw the boundary inside the module first (group each responsibility into its own package or directory and keep the cross-boundary members non-public), since splitting a published package moves types between packages and breaks consumers.

D28 · Secrets (history) · Rotate the exposed credentials · ×1

REDACTED

D34 · Knowledge Freshness · Further orphaned files (smaller) · ×1

Further orphaned files (smaller) — 180 smaller file(s) also have no living knowledge — folded into the freshness score and metrics rather than raised one row each — most significant first: spark/src/main/scala/org/apache/spark/sql/delta/skipping/clustering/ClusteredTableUtils.scala, hudi/src/main/scala/org/apache/spark/sql/delta/hudi/HudiConversionTransaction.scala, kernel/kernel-api/src/main/java/io/delta/kernel/internal/replay/PaginatedScanFilesIteratorImpl.java, spark/src/main/scala/org/apache/spark/sql/delta/stats/AutoCompactPartitionStats.scala, storage-s3-dynamodb/src/main/java/io/delta/storage/S3DynamoDBLogStore.java, kernel/kernel-api/src/main/java/io/delta/kernel/internal/rowtracking/RowTracking.java, spark/src/main/scala/org/apache/spark/sql/delta/expressions/HilbertIndex.scala, spark/src/main/scala/org/apache/spark/sql/delta/expressions/InterleaveBits.scala (and 172 more) (188 orphaned of 795 analysed files in total, counted over production source files of roughly 2,400 bytes or more, excluding vendored, generated, example/demo and scaffolding-template trees and test files identified by path convention, largest first; 795 of the 1126 production source files in this repository met that bar). Attach the read to the next change that touches one of them: have a second person review that change, and leave behind a short comment or test recording what the file is for, so the knowledge comes back at the cost of a change you were making anyway.

D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

D36 · Supply-chain Provenance & Signing · REDACTED · ×1

REDACTED

M2 · Architecture documentation · ADRs not easily discoverable · ×1

ADRs not easily discoverable — 4 ADR-shaped document(s) detected by content — `protocol_rfcs/concurrent-identity-columns.md`, `protocol_rfcs/file-type.md`, `protocol_rfcs/iceberg-v4-metadata.md`, `protocol_rfcs/template.md`. They are not under a conventional ADR folder (docs/adr/) and are not named NNNN-title.md, and this check found them by their decision signature rather than by where they live — so a reader who does not already know these paths has no route to them. Detected by content signature only: records kept outside the repository, or written without a Status/Decision/Consequences shape, are not visible to this check and are not counted here.

P2 · Observability · Logging is not universal · ×1

Logging is not universal — Only 1/3 runnable modules use logging (modules with no entry point or server are excluded — they are libraries a runnable module hosts). Silent: `.`, `dev`.

P4 · Deployment & Rollback · No rollback/health safety · ×1

No rollback/health safety — Deployment is orchestrated by compose, but no service declares a `healthcheck:` and nothing pins a previous image to fall back to — the runtime can tell that the container is up, not that it is serving, so a bad release is harder to detect and reverse.

PF1 · Benchmark discipline · Benchmarks don't track allocations · ×1

Benchmarks don't track allocations kernel/kernel-benchmarks/src/test/java/io/delta/kernel/benchmarks/BenchmarkParallelCheckpointReading.java — A JMH/Jetpack Benchmark suite exists but nothing turns on its allocation measurement — allocations (the main way hot code pressures a garbage collector or allocator) aren't being measured.

X23 · Unguarded diagnostic materialisation · Diagnostic log message is built whether or not it is wanted · ×1

Diagnostic log message is built whether or not it is wanted flink/src/main/java/io/delta/flink/sink/DeltaSinkWriter.java:101 — `debug` at line 101 is called with an argument built by `Arrays.toString(conf.getPrimaryKeyOrdinals())` (line 104), whose cost grows with the collection it walks. Java evaluates a call's arguments BEFORE entering the method, so that join/projection runs in full every time this line is reached — and then the level check inside the logger discards the string it produced, because debug is a level a shipped configuration normally leaves off. Nothing here decides beforehand whether the message is wanted: no `isDebugEnabled`/`isTraceEnabled` test, no debug flag, no lambda or `Supplier` the logger calls only when the level is on.

X5 · Nullable reference types · Scala's null is not held to the type system everywhere · ×1

Scala's null is not held to the type system everywhere — No build over this repository's 502 Scala product file(s) passes `-Yexplicit-nulls`, enables WartRemover's `Null` wart or runs Scalafix's `DisableSyntax.noNulls`, so every reference type admits null and nothing reports a `null` written into the code or returned from a Java API — the first one to reach a method call is a `NullPointerException`. `Option` by convention is a habit no tool here holds the code to.

X7 · Silent fallback defaults · Silent fallback default in catch · ×1

Silent fallback default in catch spark/src/main/scala-shims/spark-4.1-4.3/VariantShreddingShims.scala:59 — `extractAndInjectVariantStats` swallows every exception into `` — a data error becomes a silent behavior change with no trail. Log the failure or let it propagate. If that constant is the correct answer rather than a stand-in for a value that could not be read, say so in a comment in the catch case or in the Scaladoc, and the row stops firing.

Minor — 1 finding(s)

D5 · Coupling · Off the main sequence · ×1

Off the main sequence: connectCommon — connectCommon: abstractness 0.00, instability 0.00, distance 1.00 — the shape a shared-kernel / building-block library has BY DESIGN — concrete and widely depended-on is what makes it useful, and this dimension does not penalise it (the distance is reported for completeness, not as a defect). Worth a look only if it has grown past one coherent kernel into an everything-bucket.

Appendix B — Reproduction & audit trail

Every external tool invocation behind a deep-scan dimension — the tool, its captured version, the exact command, how many findings it yielded, and a link to the retained raw output. To reproduce any finding: check out the same commit and run the command shown (repo-relative — never an absolute scratch path). The complete raw scanner output is retained verbatim under artifacts/raw/ (indexed in artifacts/raw/index.json); per-invocation exit codes and wall-clock durations are in sidecar.json — kept out of this table so the rendered report stays byte-identical across runs of the same commit.

Dimension	Tool	Version	Command	Findings	Raw output
D28 · Secrets (history)	gitleaks	—	gitleaks detect --no-banner --config /opt/gitleaks-rules/watchdog-gitleaks.toml --report-format json --report-path /tmp/watchdog-gitleaks-de6aa2dc07514153b08bbfa579e2f6dd/history.json --exit-code 0 --source .	2	artifacts/raw/gitleaks-history.json
D28 · Secrets (history)	gitleaks	—	gitleaks detect --no-git --no-banner --config /opt/gitleaks-rules/watchdog-gitleaks.toml --report-format json --report-path /tmp/watchdog-gitleaks-de6aa2dc07514153b08bbfa579e2f6dd/tree.json --exit-code 0 --source .	0	artifacts/raw/gitleaks-tree.json
D29 · Static Analysis (SAST)	semgrep	—	semgrep --config /opt/semgrep-rules/security-audit.yml --config /opt/semgrep-rules/owasp-top-ten.yml --config /opt/semgrep-rules/watchdog-sast.yml --json --quiet --timeout 10 --timeout-threshold 3 --metrics off --exclude .arrow --exclude .avro --exclude .csv --exclude .dat --exclude .db --exclude .feather --exclude .geojson --exclude .h5 --exclude .hdf5 --exclude .jsonl --exclude .log --exclude .ndjson --exclude .npy --exclude .npz --exclude .orc --exclude .parquet --exclude .pickle --exclude .pkl --exclude .psv --exclude .sqlite --exclude .sqlite3 --exclude .tfrecord --exclude .tsv --exclude .txt --exclude spark/src/test/scala/org/apache/spark/sql/delta/generatedsuites/delete --exclude spark/src/test/scala/org/apache/spark/sql/delta/generatedsuites/merge --exclude spark/src/test/scala/org/apache/spark/sql/delta/generatedsuites/mergeamt --exclude spark/src/test/scala/org/apache/spark/sql/delta/generatedsuites/update .	11	artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilities	trivy	—	trivy fs --scanners vuln --format json --quiet --severity CRITICAL,HIGH,MEDIUM,LOW --skip-dirs /bin/ --skip-dirs /obj/ . --skip-db-update	4	artifacts/raw/trivy-fs.json
D31 · IaC & Container Security	trivy	—	trivy config --format json --quiet .	4	artifacts/raw/trivy-config.json
D32 · Data Compliance (PII/GDPR)	semgrep	—	semgrep: not applicable — No personal data was found crossing a boundary the PII/GDPR ruleset checks — nothing written to a log or console sink, placed in a URL or query string, or persisted to browser storage. That is a clean result for the LEAK surface only: this ruleset detects personal data escaping, it does not inventory the personal data a repository holds, so it is not evidence that this repository has no personal-data surface. The personal-data map (Appendix C) and the C1-C5 compliance cards are what speak to that. semgrep could not parse 2 file(s) — `spark/src/main/scala/org/apache/spark/sql/delta/actions/actions.scala`, `spark/src/main/scala/org/apache/spark/sql/delta/sources/DeltaSourceOffset.scala` — so the PII/GDPR sweep did not cover them at all.	0	—
D37 · Vulnerability-disclosure Policy	disclosure	—	disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.	0	—
D40 · Network Egress Confinement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.	0	—
D41 · Kernel & Syscall Confinement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.	0	—
D42 · Runtime Threat Enforcement	runtime-hardening	—	runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.	0	—
D43 · Malicious Dependencies	trivy	—	trivy fs --scanners vuln --format json --quiet --severity CRITICAL,HIGH,MEDIUM,LOW --skip-dirs /bin/ --skip-dirs /obj/ . --skip-db-update	0	artifacts/raw/trivy-fs.json

Run 01a176c7-def1-7679-bc11-5644f3b5d0f0 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Findings by how serious they are

This survey was produced by

Executive summary

Top priorities

Diagnosis: what the measurements show together

Architecture — module dependency graph

Architecture: which parts of the code depend on which

At a glance — Code Health · 62% · Adequate · gated by X5 ·

At a glance — Architecture · 87% · Adequate · gated by D26 ·

At a glance — Maturity · 71% · Strong ·

At a glance — Readiness · 62% · Adequate ·

At a glance — Security · 77% · Adequate · gated by D29 ·

At a glance — Performance · 78% · Strong ·

Security & Compliance — OWASP Top-10 mapping

Roadmap

File quality

How the grades work

Methodology & how to trust this report

Tools & methods

Run transparency — what happened this run

Limitations & what we did not check

Per-dimension blind spots

Dimensions

Frontend & cross-cutting dimensions

Reference — by lens

Appendix A — Findings (grouped)

Appendix B — Reproduction & audit trail

Downloadable artifacts