chronon — Watchdog Audit

Executive summary

Preview (pre-1.0). This repo hasn't declared a stable release, so it's judged against a relaxed, pre-production bar.

The system holds an adequate overall standing of 54%, indicating a workable asset that carries significant operational risk. While the codebase is well-structured and maintainable, its readiness for production is critically low. This gap exposes the business to potential outages and security regressions that could disrupt service reliability and increase incident response costs.

The asset is of medium size, comprising over thirty thousand lines of production code and nearly thirty thousand lines of tests. Rebuilding this logic from scratch would require approximately half a person-year of effort, valued at roughly €74,000. This substantial investment underscores the importance of protecting the existing codebase through improved operational safeguards rather than considering a costly replacement.

The primary risk lies in operational fragility. With a readiness score of only 39%, the system lacks essential safety nets such as automated health checks and documented disaster recovery procedures. Without these, a failure could lead to extended downtime and data loss, as there is no verified process for rapid restoration. This vulnerability directly threatens business continuity and customer trust.

A secondary concern is security exposure. The current security posture scores 62%, which is insufficient for a system of this scale. The absence of automated static analysis in the delivery pipeline means that security flaws can slip into production unnoticed. This creates a latent liability, increasing the likelihood of future breaches or compliance violations that could result in financial penalties and reputational damage.

On the positive side, the code health is strong at 85%, and the architecture is reasonably sound at 76%. The code is clean, modular, and easy for new engineers to understand. This high quality provides a solid foundation for improvement, ensuring that remediation efforts will be effective and sustainable.

The immediate focus should be integrating automated security scanning into the CI pipeline. This single action offers the highest leverage by preventing future security regressions at minimal cost. It is a quick win that addresses a critical gap without requiring significant architectural changes, allowing the team to build confidence before tackling more complex operational improvements.

Code Health 85% Strong Architecture 76% Adequate · gated by D26 Maturity 70% Strong Readiness 39% Weak · gated by P3, P5 Security 62% Adequate · gated by D29, D31, D36

How the score is built — each lens's share of the headline Width is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.

Readiness 39% · 47% weightSecurity 62% · 26% weightMaturity 70% · 14% weightArchitecture 76% · 8% weightCode Health 85% · 4% weight

Raise Readiness 39 → 70 (the Healthy floor) ⇒ headline 54 → ~67.

Code composition — where the lines go

Tests 100%

New since the last scan (10+)

10 finding(s) are new versus the previous scan (2026-09-11) — surfaced by this scheduled scan itself, no pull request required.

D2 · explore.enrich_with_joins (cognitive 17) REDACTED
D4 · Duplicated block (6 lines × 2) online/src/main/java/ai/chronon/online/TBaseDecoderFactory.java
D4 · Duplicated block (17–19 lines × 2) airflow/decorators.py
D4 · Duplicated block (16–17 lines × 2) api/py/ai/chronon/pyspark/executables.py
D4 · Duplicated block (12–13 lines × 3) api/py/ai/chronon/pyspark/executables.py
D4 · Duplicated block (10–11 lines × 2) airflow/helpers.py
D4 · Duplicated block (9 lines × 2) api/py/ai/chronon/lineage/lineage_parser.py
D4 · Duplicated block (8 lines × 2) api/py/ai/chronon/repo/compile.py
D4 · Duplicated block (10 lines × 2) airflow/group_by_dag_constructor.py
D4 · Duplicated block (13 lines × 2) api/py/ai/chronon/group_by.py

A full-fidelity diff against the previous run's complete recorded findings — line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.

Rebuild cost & value ~ Modeled — €25,000–€120,000

Cost to rebuild	€25,000–€120,000 (0.2–0.8 person-years (411–1,304 h), ~1 engineer)
Domain complexity	Standard — harder problems cost more per line
Quality factor	0.8× (at 54% quality) — the last 20% of quality is most of the work
Size & shape	Medium · effort split not classified (source measured from disk; the effort-tier breakdown is a C#-only syntax walk)

This codebase represents roughly ~0.5 person-years of build effort (about ~€74,000 to rebuild). Its weakest lens is Readiness at 39% — the part of that asset most exposed by the findings below.

How we model this: boilerplate at a scaffolding rate + logic × domain Standard (×1.2) — CQRS × a 0.8× quality factor, at €60–95/h; indicative, ±~30% · size measured directly from source · effort from total production LoC as straight-line logic (the tier split is a C#-only syntax walk), a conservative lower bound. Indicative only — most sensitive to the hourly rate and the domain tier (both tunable in config).

Top priorities

The highest-leverage moves; the full ranked list is in the Roadmap below.

Add a SAST step to CI running what this repository's stack ships: scalafix or scapegoat — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.

+15.3 pts · Medium effort · Security & performance tooling

Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.

+15.3 pts · Medium effort · DR & Backup

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.

+14.8 pts · Medium effort · Deployment & Rollback

Diagnosis — what's actually going on

Value concentrated against a weak lens · High · Value at risk

This is a Medium asset (~0.5 person-years to rebuild), and its weakest lens is Readiness at 39%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.

Evidence: valuation: Medium, ~0.5 person-years rebuild (33,736 LoC) · weakest lens: Readiness 39%

→ Direct remediation budget at Readiness first — highest risk-reduction per euro on an asset this size.

Highest-leverage move · Medium · Leverage

Of everything flagged, the best return on effort is: Add a SAST step to CI running what this repository's stack ships: scalafix or scapegoat — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing. The rest can wait behind it.

Evidence: priority ranking: top of 5 ranked by impact/effort

→ Add a SAST step to CI running what this repository's stack ships: scalafix or scapegoat — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.

Architecture — module dependency matrix

Rows and columns are the same modules, ordered so that a module only depends on ones above it. A cell means the row depends on the column, and its number is how many type pairs create that dependency. Read one thing: is anything above the diagonal? A mark there is a dependency cycle. (A cycle is all this shows — an unusual but cycle-free dependency sits below the diagonal like any other.)

97 modules, 140 dependencies. 2 dependency cycles across 9 modules, marked above the diagonal.

Showing the 40 most-connected modules; 57 more are not drawn.

Module dependency matrix. The row depends on the column; the number is how many type pairs create the dependency. A cell above the diagonal is part of a dependency cycle.
depends on →	1 aggregator.row.StatsGenerator	2 online.FetcherCache.BatchIrCache	3 online.KVStore	4 api.Builders	5 api	6 online.FetcherModelUtils	7 online.Metrics	8 aggregator.base	9 api.Extensions	10 online.CatalystUtil	11 spark.catalog	12 aggregator.row	13 spark.Extensions	14 aggregator.windowing.TwoStackLiteAggregator	15 aggregator.windowing	16 online.FetcherCache	17 spark	18 online.serde	20 online.Fetcher	21 online	22 flink.window	26 spark.Driver	28 spark.streaming.JoinSourceRunner
1 aggregator.row.StatsGenerator
2 online.FetcherCache.BatchIrCache
3 online.KVStore
4 api.Builders					3
5 api				1
6 online.FetcherModelUtils				1
7 online.Metrics				4																1
8 aggregator.base					17
9 api.Extensions				17	8
10 online.CatalystUtil					1
11 spark.catalog				1	4								1				1
12 aggregator.row	1			2	16			1
13 spark.Extensions					4						2						5	1
14 aggregator.windowing.TwoStackLiteAggregator												1
15 aggregator.windowing				2	5				1			1		1
16 online.FetcherCache		1	1												1
17 spark				20	18		3	1			8	1	2		3			1		2
18 online.serde					12												1
19 online.Extensions					1													1
20 online.Fetcher				1	1		3											1		1
21 online		1	2	13	11	1	5		2	1		1			3	4	1	4	14
22 flink.window				1	1		1					1								1
23 online.ExternalSourceRegistry																			2	1
24 online.FetcherBase			1				1													1
25 quickstart.online			3	1	4															12
26 spark.Driver											3						19			2
27 spark.stats	1			1	2						3	2					1			1
28 spark.streaming.JoinSourceRunner			1		3															1
29 flink			4	2	1			1												6	1
30 spark.Driver.CompareJoinQuery				2																		1
31 spark.Driver.DailyStats				1																		1
32 spark.Driver.GroupByBackfill				1																		3
33 spark.Driver.JoinBackfill				1																		4
34 spark.Driver.JoinBackfillFinal				1																		4
35 spark.Driver.JoinBackfillLeft				1																		4
36 spark.Driver.LabelJoin				1																		2
37 spark.Driver.LogFlattener				1																		1
38 spark.Driver.LogStats				1																		1
39 spark.Driver.ModelTransformBatch				1																		2
40 spark.streaming			3	3	2		1													11			1

Dependency, pointing down the layeringAbove the diagonal — part of a cycleThe module itself

At a glance — Code Health · 85% · Strong ·

The Good

D3 · Scala God Classes 8.2 D4 · Scala Code Duplication 9.7 D17 · Scala Explicit Debt 9.7

The Bad

D1 · Scala Cyclomatic Complexity 6.3 D2 · Scala Cognitive Complexity 6.4

At a glance — Architecture · 76% · Adequate · gated by D26 ·

The Good

D6 · Scala Cohesion (LCOM4) 8.7 D35 · Scala Change Coupling 10.0 AX10 · Repo Code composition 7.1 AX5 · Repo Architecture & structure 10.0

The Ugly

D26 · Scala Project Cohesion 0.0

At a glance — Maturity · 70% · Strong ·

The Good

D15 · Scala Churn × Complexity Hotspots 10.0 D16 · Scala Bus Factor 9.6 D19 · Scala Documentation Quality 9.2 D21 · Scala Naming Consistency 10.0 M3 · Repo Folder & project structure 10.0 M4 · Repo Documentation accuracy 10.0

The Bad

D34 · Scala Knowledge Freshness 4.5 M1 · Repo Documentation (README) 6.0 M2 · Repo Architecture documentation 5.0

The Ugly

D20 · Scala ADR Quality 0.0

At a glance — Readiness · 39% · Weak · gated by P3, P5 ·

The Good

D9 · Scala Test Distribution 10.0 D12 · Scala Dependency Hygiene 9.3 D13 · Scala Secret Scanning 10.0 D14 · Scala License Compliance 10.0 P1 · Repo CI/CD gates 10.0 P2 · Repo Observability 10.0

The Bad

P4 · Repo Deployment & Rollback 5.0 P6 · Repo Release Hygiene 5.0

The Ugly

P3 · Repo Security & performance tooling 0.0 P5 · Repo DR & Backup 0.0

At a glance — Security · 62% · Adequate · gated by D29, D31, D36 ·

The Good

D28 · Scala Secrets (history) 10.0 D43 · Scala Malicious Dependencies 10.0 D44 · Scala Platform End-of-Life 10.0

The Bad

D30 · Scala Dependency Vulnerabilities 6.6

The Ugly

D29 · Scala Static Analysis (SAST) 0.2 D31 · Scala IaC & Container Security 3.2 D36 · Scala Supply-chain Provenance & Signing 3.3

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
A05:2021 — Security Misconfiguration	30	High / Critical
A03:2021 — Injection	24	High / Critical
A06:2021 — Vulnerable & Outdated Components	9	High / Critical

Roadmap

First, integrate automated security scanning into the CI pipeline to block regressions and resolve existing tainted SQL findings. Second, codify disaster recovery and backup procedures in infrastructure-as-code while documenting recovery objectives. Third, implement health checks and immutable image tags to ensure reliable deployments and simple rollbacks. Finally, maintain a changelog to track release history and improve release hygiene.

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

Do this	Helps	Effort	Dimension
Add a SAST step to CI running what this repository's stack ships: scalafix or scapegoat — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.	+15.3 pts	Medium	Security & performance tooling
Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.	+15.3 pts	Medium	DR & Backup
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.	+14.8 pts	Medium	Deployment & Rollback
Keep a changelog (e.g. Keep-a-Changelog) recording what shipped in each release.	+14.8 pts	Medium	Release Hygiene
Resolve the 1 No ADRs found finding(s) in ADR Quality.	+2.2 pts	Low	ADR Quality
Resolve the 2 Most significant orphaned file finding(s) in Knowledge Freshness — start with SimpleAggregators.scala, executables.py.	+1.4 pts	Low	Knowledge Freshness
Resolve the 1 Projects may be oversized for their cohesion finding(s) in Project Cohesion.	+1.4 pts	Low	Project Cohesion
Resolve the 16 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (10), REDACTED (2), REDACTED (2).	+2.3 pts	Medium	Static Analysis (SAST)

File quality

Per-file score 0–10 — a quality signature. Of 71 files carrying findings, judged against the Preview bar: 7% slop · 34% mixed · 59% near-clean.

File	Score	Band	Worst signal
REDACTED	0.0	Slop	Static Analysis (SAST): High: REDACTED
REDACTED	0.0	Slop	IaC & Container Security: High IaC: REDACTED
REDACTED	0.8	Slop	IaC & Container Security: High IaC: REDACTED
REDACTED	0.8	Slop	IaC & Container Security: High IaC: REDACTED
REDACTED	1.0	Slop	Dependency Vulnerabilities: High CVE: REDACTED
REDACTED	4.8	Mixed	IaC & Container Security: High IaC: REDACTED
REDACTED	5.0	Mixed	Static Analysis (SAST): Medium: REDACTED
REDACTED	5.1	Mixed	Static Analysis (SAST): High: REDACTED
online/src/main/scala/ai/chronon/online/Fetcher.scala	5.7	Mixed	Cyclomatic Complexity: Fetcher.logResponseInternal (cyclomatic 20)
REDACTED	5.7	Mixed	Static Analysis (SAST): High: REDACTED
REDACTED	5.8	Mixed	Static Analysis (SAST): High: REDACTED
REDACTED	5.8	Mixed	Static Analysis (SAST): High: REDACTED
REDACTED	5.8	Mixed	Static Analysis (SAST): High: REDACTED
aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala	6.0	Mixed	Explicit Debt: TodoComment
api/py/ai/chronon/group_by.py	6.0	Mixed	Explicit Debt: TodoComment
online/src/main/scala/ai/chronon/online/FetcherBase.scala	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/ai/chronon/spark/FastHashing.scala	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/ai/chronon/spark/Analyzer.scala	6.0	Mixed	Explicit Debt: TodoComment
api/py/ai/chronon/join.py	6.0	Mixed	Explicit Debt: TodoComment
spark/src/main/scala/ai/chronon/spark/JoinBase.scala	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 — 42

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 — 180

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 — 32

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

Could not be resolved — 50

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. 33 of 37 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 4 documentation/naming judgement(s) are LLM-assisted and labelled advisory. 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 — 37 dimensions across the health lenses

D1D2D3D4D6D9D12D13D14D15D16D17D19D20D21D26D28D29D30D31D34D35D36D43D44AX10AX5M1M2M3M4P1P2P3P4P5P6

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, 227 of 254 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	Local LLM	◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 01a0e932-1aec-76da-9371-4c2590cba282.

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.

D5 Coupling — 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.
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 (.scala, .py) 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 (`addSbtPlugin("org.scoverage" % "sbt-scoverage" % "<version>")` in `project/plugins.sbt`, then `sbt clean coverage test coverageReport`, or `coverage run -m pytest` then `coverage xml`) 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 (`addSbtPlugin("org.scoverage" % "sbt-scoverage" % "<version>")` in `project/plugins.sbt`, then `sbt clean coverage test coverageReport`, or `coverage run -m pytest` then `coverage xml`) 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 source is present (.scala, .py) and this repository declares an sbt build (repository root, 96 test files), but it was not re-run: the analyzer environment could not run it. Not scored — this is a gap in the analyzer's language coverage, not a finding about this repository.
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 (build.sbt), but the licence verdict published here was taken over its Python distribution 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.
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 identifies the intentionally-exposed surface from `IsPackable` and `.Contracts` project names, MSBuild conventions read off the loaded project set. This target exposed no such projects, so the probe never ran; this says nothing about whether the repository has a public API. This repository commits no C#/VB source at all, so there was never an MSBuild project set to read these conventions off. That is OUR side and it is a COLLECTOR gap, not an environment fault: it declares a published package (api/py/setup.py), but no published-package marker D22 reads admitted any project here, so this ecosystem's public API has no collector, and the remedy is to write one — no change to the scan image can close it.
AX1 Captive dependencies — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
AX2 Stateful singletons — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
AX3 Project dependency cycles — 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 is computed over which project references which. That is a language-neutral question, but the project-reference graph is collected from MSBuild .csproj, Gradle, Maven, Cargo, npm/pnpm/yarn, Go module, Python pyproject.toml and SwiftPM builds only, and this repository commits none — so there was no graph to read, and re-running the same commit reads the same nothing. Its modules are declared as: sbt subprojects (build.sbt); Python distributions declared in setup.py/setup.cfg (a pyproject.toml [project] or [tool.poetry] table is read; these are not); Bazel packages (BUILD, MODULE.bazel). A reader for that graph is the collector this check is missing. That is a COLLECTOR gap in this analyzer — no change to the scan image closes it — and not a finding that the repository is free of what this check looks for.
AX6 Interface segregation — 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 is computed over the public interfaces this run's compilations declare, and none was loaded, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
AX8 Test isolation — 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 is computed over which projects are test projects, and what they reference. That is a language-neutral question, but the project-reference graph is collected from MSBuild .csproj, Gradle, Maven, Cargo, npm/pnpm/yarn, Go module, Python pyproject.toml and SwiftPM builds only, and this repository commits none — so there was no graph to read, and re-running the same commit reads the same nothing. Its modules are declared as: sbt subprojects (build.sbt); Python distributions declared in setup.py/setup.cfg (a pyproject.toml [project] or [tool.poetry] table is read; these are not); Bazel packages (BUILD, MODULE.bazel). A reader for that graph is the collector this check is missing. That is a COLLECTOR gap in this analyzer — no change to the scan image closes it — and not a finding that the repository is free of what this check looks for.
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.
ED5 Idempotency — 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 finds retry-prone mutations by walking the repository's declared types, and NONE was loaded on this run, so it had nothing to look at. That is a limit of the analyzer's reach — it reads .NET projects — not a finding that this repository has no command handlers or message consumers.
GD1 Unfinished & placeholder code — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
IC1 Incompleteness & stubs — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
P10 Library API & versioning — 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 reads NuGet packaging and C# public API only, and no .NET project was loaded for this repository, so it had nothing of this repository's product to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
PF1 Benchmark discipline — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
PF2 Allocation 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. This check is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
PF3 Async & latency 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. Those languages colour their functions async, so blocking inside them is the same defect this card counts elsewhere, but their blocking vocabulary is not modelled yet. That is a gap in this analyzer's language reach — not a finding that the code is free of it.
S1 Web-Security Posture — 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 web-security 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 web-security controls.
X1 Async correctness — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X10 Duplicated predicate — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X12 Unreachable branch — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X13 Undrained process stream — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X14 Bypassable address classification — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X15 Unvalidated length from an untrusted reader — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X16 Unfloored truncation loop — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X17 Uncapped recursion over a caller-supplied document — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X18 Disposal-pattern correctness — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X19 Unrestored process-global state — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X2 Cancellation propagation — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X20 Mistyped argument guard — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X21 Side-effecting pattern guard — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X22 Contradicted release guard — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X23 Unguarded diagnostic materialisation — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X24 Document value interpolated into markup unescaped — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X25 Inert configuration knob — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X26 Unsynchronised callback handoff — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X27 Collection changed while being enumerated — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X28 Index access outside its own emptiness guard — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X29 Per-element action decided by a fixed element — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X3 Exception handling — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X30 Support guard that admits what it rejects — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X32 Type resolved by simple name across every loaded assembly — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X4 Structured logging — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X5 Nullable reference types — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X6 Hand-rolled structured-format parsing — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.
X7 Silent fallback defaults — 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 is implemented over the C# syntax tree, and no C# was loaded on this run, so it had nothing to read. That is a gap in this analyzer's language reach — not a finding that the repository is free of what this check looks for.

Repo exclusion declarations (.gitattributes linguist-generated/vendored, .editorconfig generated_code): none declared — every source file was scored.

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.
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.
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.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles — a vulnerability in a vendored/copied dependency, or risk from how a dependency is actually used, is outside this view.
D13 Secret Scanning: Secret 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 is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement. Its critique rows are drawn from a closed category vocabulary and each row means the same thing in every run, so two scans can be compared row by row; the SET that fires is still a sample, and does not repeat exactly. Measured on one frozen input, six scans at one engine SHA: 2-5 critique rows per scan, 8 distinct rows across the six, 3 of those 8 seen in only one scan. So a D19 row is evidence about the documentation, but a COUNT of D19 rows is not a quantity — never read a change in it as an improvement or a regression.
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.
D21 Naming Consistency: Naming quality is an LLM judgement over a bounded sample — it assesses clarity/consistency of the names it sees, not domain-correctness, and is 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.

The LLM boundary

LLM-set scores this run (4): D19, D21, D26, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score; each names its own sample and method on its card. They are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.

Dimensions

D1 · Cyclomatic Complexity6.3 / 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 6.3 / 10 · rule-coverage 100% · ceiling Prevented

20 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was ColumnAggregator.construct at 106. A further 6 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 Driver.main at 21 — they are counted neither in the figure above nor in this dimension's score. 4 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: spark/src/main/scala/ai/chronon/spark/Driver.scala (Driver.main at 21), api/src/main/scala/ai/chronon/api/DataType.scala (DataType.fromTDataType at 18), online/src/main/scala/ai/chronon/online/serde/AvroConversions.scala (AvroConversions.toChrononSchema at 17), online/src/main/scala/ai/chronon/online/serde/SparkConversions.scala (SparkConversions.fromChrononType at 16). 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.

ColumnAggregator.construct (cyclomatic 106)aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:227

group_by.validate_group_by (cyclomatic 33)api/py/ai/chronon/group_by.py:221

SparkInternalRowConversions.to (cyclomatic 26)online/src/main/scala/ai/chronon/online/SparkInternalRowConversions.scala:130

Row.to (cyclomatic 25)api/src/main/scala/ai/chronon/api/Row.scala:130

FetcherBase.fetchGroupBys (cyclomatic 24)online/src/main/scala/ai/chronon/online/FetcherBase.scala:353

+ 15 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 1 ColumnAggregator.construct (cyclomatic 106) finding(s) in Cyclomatic Complexity — start with ColumnAggregator.scala. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 group_by.validate_group_by (cyclomatic 33) finding(s) in Cyclomatic Complexity — start with group_by.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 SparkInternalRowConversions.to (cyclomatic 26) finding(s) in Cyclomatic Complexity — start with SparkInternalRowConversions.scala. — One of this dimension's main actionable groups (1 warning-level).
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 Complexity6.4 / 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 6.4 / 10 · rule-coverage 100% · ceiling Prevented

49 method(s) exceeded the cognitive complexity threshold of 15; the worst was LineageParser.parse_join at 56.

LineageParser.parse_join (cognitive 56)api/py/ai/chronon/lineage/lineage_parser.py:429

group_by.validate_group_by (cognitive 52)api/py/ai/chronon/group_by.py:221

ColumnAggregator.construct (cognitive 49)aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:227

run.set_runtime_env (cognitive 48)REDACTED:239

compile.extract_and_convert (cognitive 43)api/py/ai/chronon/repo/compile.py:90

+ 44 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 1 LineageParser.parse_join (cognitive 56) finding(s) in Cognitive Complexity — start with lineage_parser.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 group_by.validate_group_by (cognitive 52) finding(s) in Cognitive Complexity — start with group_by.py. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 ColumnAggregator.construct (cognitive 49) finding(s) in Cognitive Complexity — start with ColumnAggregator.scala. — One of this dimension's main actionable groups (1 warning-level).
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 Classes8.2 / 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 8.2 / 10 · rule-coverage 100% · ceiling Prevented

14 god class(es) detected.

FileTooLong: spark/Driver.scala · ×11spark/src/main/scala/ai/chronon/spark/Driver.scala

ClassTooLong: JoinSourceRunner · ×2spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:91

MethodTooLong: Row.toapi/src/main/scala/ai/chronon/api/Row.scala:130

What to do

Resolve the 11 FileTooLong finding(s) in God Classes — start with Driver.scala, REDACTED, REDACTED. — One of this dimension's main actionable groups (11 warning-level).
Resolve the 2 ClassTooLong finding(s) in God Classes — start with JoinSourceRunner.scala, JoinBase.scala. — One of this dimension's main actionable groups (2 warning-level).
Resolve the 1 MethodTooLong finding(s) in God Classes — start with Row.scala. — One of this dimension's main actionable groups (1 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.

Do you agree with this assessment?

D4 · Code Duplication9.7 / 10Stronggated by 22 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 9.7 / 10 · rule-coverage 100% · ceiling Verified

22 duplicated block group(s) detected.

Duplicated block (9 lines × 2) · ×3flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:91

Duplicated block (5 lines × 2) · ×3spark/src/main/scala/ai/chronon/spark/GroupBy.scala:821

Duplicated block (10 lines × 2) · ×2online/src/main/scala/ai/chronon/online/FetcherBase.scala:151

Duplicated block (8 lines × 2) · ×2quickstart/mongo-online-impl/src/main/scala/ai/chronon/quickstart/online/QuickstartMutationDecoder.scala:47

Duplicated block (7 lines × 2) · ×2api/src/main/scala/ai/chronon/api/Extensions.scala:624

+ 10 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

Resolve the 3 Duplicated block (9 lines × 2) finding(s) in Code Duplication — start with FlinkJob.scala, CatalystUtil.scala, lineage_parser.py. — One of this dimension's main actionable groups (3 warning-level).
Resolve the 3 Duplicated block (5 lines × 2) finding(s) in Code Duplication — start with GroupBy.scala, JoinBase.scala, Analyzer.scala. — One of this dimension's main actionable groups (3 warning-level).
Resolve the 2 Duplicated block (10 lines × 2) finding(s) in Code Duplication — start with FetcherBase.scala, group_by_dag_constructor.py. — One of this dimension's main actionable groups (2 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.

Do you agree with this assessment?

D6 · Cohesion (LCOM4)8.7 / 10Strong✓ 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 8.7 / 10 · rule-coverage 100% · ceiling Verified

6 of 55 classes have LCOM4 above 3.

Low cohesion: SourceOps (LCOM4 8) · ×6api/src/main/scala/ai/chronon/api/Extensions.scala:312

What to do

Resolve the 6 Low cohesion finding(s) in Cohesion (LCOM4) — start with REDACTED (3), SimpleAggregators.scala, TimedAggregators.scala. — One of this dimension's main actionable groups (6 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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D9 · Test Distribution10.0 / 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

158 test methods: 158 unit, 0 integration, 0 BDD, 0 e2e. The Python suite contributes 150 test function(s) across 18 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.

✓ On the Gold path — maintain.

Detailed fixes: d9_recommendation.md.

Do you agree with this assessment?

D12 · Dependency Hygiene9.3 / 10Exemplary✓ Tool-verified

What it measures: Whether dependencies are current, secure, and not bloated.

Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.

Maturity: Documented → Verified → Prevented · effective 9.3 / 10 · rule-coverage 100% · ceiling Verified

14 outdated direct sbt declarations. An sbt declaration names an EXACT version, so the remedy is an edit to the build file — there is no lockfile refresh that would move it. Test-, Provided- and it-scoped declarations are excluded, because a consumer of this project never receives them. A version held in a Scala val is not read: sbt is a program rather than a manifest, and evaluating one would invent the measurement rather than take it. Whether any artifact is DEPRECATED or ABANDONED is not graded and cannot be — Maven Central publishes no such marker, and release age does not stand in for one: the most widely depended-upon libraries are routinely the stalest, being finished rather than abandoned. Known CVEs in this dependency graph are D30's question.

Outdated: ch.qos.logback:logback-classic · ×14

✓ On the Gold path — maintain.

Detailed fixes: d12_recommendation.md · top locations in Appendix A, every location in findings.md.

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D13 · Secret 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

Secret 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 126 shipped Python distribution(s) use a banned license. Licences were resolved from PyPI over the distributions a consumer installs — this repository's 38 declared runtime requirement(s) closed transitively over each distribution's published `requires_dist` (88 reached that way). Requirements it states ONLY under an extra, a PEP 735 dependency group, a Poetry dev group or a dev-named requirements file are excluded: pip does not install any of them for a consumer. ★ This repository commits no dependency lockfile that this pass reads, so each licence is the one PyPI publishes for the distribution's CURRENT release rather than for a pinned version. 31 of them publish no licence on PyPI this pass can read; that is missing data, not a violation, and none of them is charged. ★ COVERAGE OF THIS VERDICT: it grades this repository's Python distribution dependencies and nothing else. The repository also declares an sbt build (build.sbt), and the licences of those dependencies 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.

Do you agree with this assessment?

D15 · Churn × Complexity Hotspots10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

No churn × complexity hotspots in the window.

✓ On the Gold path — maintain.

Detailed fixes: d15_recommendation.md.

Do you agree with this assessment?

D16 · Bus Factor9.6 / 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 9.6 / 10 · rule-coverage 100% · ceiling Documented

5 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is REDACTED. Counted over 129 of the 212 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

Off-boarding risk: anonymized user #1

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.

Do you agree with this assessment?

D17 · Explicit Debt9.7 / 10Stronggated by 51 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

51 deducted task-comment markers across 33736 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 · ×51aggregator/src/main/scala/ai/chronon/aggregator/base/TimedAggregators.scala:139

What to do

Resolve the 51 TodoComment finding(s) in Explicit Debt — start with GroupBy.scala (4), REDACTED (3), GroupByUpload.scala (3). — One of this dimension's main actionable groups (51 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 QualityExemplary◐ Sampled · advisory

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

Method: Judged by language model at low temperature (0.0-0.1) on a deterministic doc sample (READMEs plus first 25 architecture docs), with two-pass stability filtering. Advisory, sampled.

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

Chronon's documentation is clear, complete, and well-structured. The root README gives a strong overview of the platform (what it does, its value proposition), a high-level architecture diagram, and an outline that lists every visible section (Platform Features; Quickstart; Requirements; Setup; Introduction; Raw data sources; Start a shell session in the Docker container; Chronon Development; Step 1 - Define some features; Step 2 - Join the features together; Step 3 - Backfilling Data; Online Flows; Uploading data; Upload Join Metadata; Fetching Data; Log fetches and measure online/offline consistency; Conclusion; Benefits of Chronon over other approaches; The log-and-wait approach; The replicate offline-online approach; Contributing; Adoption; Support) before the document is clipped. Each README documents its own directory (airflow/readme.md, service/README.md, api/py/README.md), so the root README's overview/installation/usage/contributing/licence are judged against it and found present. Chronon's documentation is clear and complete for an open-source feature platform: the README (root) gives an overview, installation/usage, and contribution guidance; architecture/design docs cover Join, GroupBy, Bootstrap, Chaining Features, Derived Features, and the timeline of backfills. The authoring_features directory is a wall-to-wall reference guide with every section named in its outline, making it self-contained for insiders. The prose is well-structured across all documents. Chronon's documentation is clear, complete, and well-structured. The READMEs (including the root one) give an overview of what Chronon does and where to find usage, while architecture/design docs cover features in depth. All visible documents are present and ordered by scope: a single 'Overview' document gives the project purpose, installation, and usage; the rest are feature guides with examples, diagrams, and production-ready code.

✓ On the Gold path — maintain.

Detailed fixes: d19_recommendation.md.

Do you agree with this assessment?

D20 · ADR Quality0.0 / 10Critical✓ Tool-verified

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 0.0 / 10 · rule-coverage 100% · ceiling Documented

No architecture decision records were found.

No ADRs found

What to do

Resolve the 1 No ADRs found finding(s) in ADR Quality. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d20_recommendation.md · top locations in Appendix A, every location in findings.md.

Do you agree with this assessment?

D21 · Naming ConsistencyExemplary◐ Sampled · advisory

What it measures: Whether names — types, methods, variables — are clear and consistent.

Method: Judged by language model at low temperature (0.0-0.1) on a deterministic random symbol sample (fixed size, not exhaustive), with disclosed confidence band. Advisory, sampled.

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

0 naming inconsistencies across 0 sampled symbols.

✓ On the Gold path — maintain.

Detailed fixes: d21_recommendation.md.

Do you agree with this assessment?

D26 · Project Cohesion0.0 / 10Critical✓ 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 0.0 / 10 · rule-coverage 100% · ceiling Documented

1 of 2 build units (sbt) 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)10.0 / 10Exemplary○ Nothing flagged

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

Method: Secret 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

gitleaks scanned the full history AND the current working tree and found no secrets.

✓ On the Gold path — maintain.

Detailed fixes: d28_recommendation.md.

Do you agree with this assessment?

D29 · Static Analysis (SAST)0.2 / 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 0.2 / 10 · rule-coverage 100% · ceiling Documented

24 finding(s): 0 critical, 21 high, 1 medium, 2 low.

REDACTED

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

What to do

Resolve the 16 REDACTED finding(s) in Static Analysis (SAST) — start with REDACTED (10), REDACTED (2), REDACTED (2). — One of this dimension's main actionable groups (16 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 (2). — 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.

Do you agree with this assessment?

D30 · Dependency Vulnerabilities6.6 / 10Adequate✓ 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/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, Go, Java and Kotlin via Maven/Gradle, 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 6.6 / 10 · rule-coverage 100% · ceiling Documented

9 finding(s): 0 critical, 4 high, 5 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).
Resolve the 5 Medium CVE finding(s) in Dependency Vulnerabilities — start with REDACTED (5). — One of this dimension's main actionable groups (5 warning-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 Security3.2 / 10Weak✓ 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 3.2 / 10 · rule-coverage 100% · ceiling Documented

30 finding(s): 0 critical, 17 high, 11 medium, 2 low.

REDACTED

What to do

Resolve the 17 High IaC finding(s) in IaC & Container Security — start with REDACTED (13), REDACTED (4). — One of this dimension's main actionable groups (17 issue-level).
Resolve the 11 Medium IaC finding(s) in IaC & Container Security — start with REDACTED (11). — One of this dimension's main actionable groups (11 warning-level).
Resolve the 2 Low IaC finding(s) in IaC & Container Security — start with REDACTED (2). — One of this dimension's main actionable groups (2 recommendation-level).

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

Do you agree with this assessment?

D34 · Knowledge Freshness4.5 / 10Weak✓ 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 4.5 / 10 · rule-coverage 100% · ceiling Documented

69 of 129 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is api/py/ai/chronon/pyspark/executables.py. Counted over 129 of the 212 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over.

Most significant orphaned file · ×2aggregator/src/main/scala/ai/chronon/aggregator/base/SimpleAggregators.scala

Concentrated knowledge decay

What to do

Resolve the 2 Most significant orphaned file finding(s) in Knowledge Freshness — start with SimpleAggregators.scala, executables.py. — One of this dimension's main actionable groups (2 recommendation-level).
Resolve the 1 Concentrated knowledge decay 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.

Do you agree with this assessment?

D35 · Change Coupling10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

No strong hidden change-coupling between production files.

✓ On the Gold path — maintain.

Detailed fixes: d35_recommendation.md.

Do you agree with this assessment?

D36 · Supply-chain Provenance & Signing3.3 / 10Weak✓ 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 3.3 / 10 · rule-coverage 100% · ceiling Documented

1/3 supply-chain integrity signals present (provenance, signing, SBOM).

REDACTED

What to do

Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 REDACTED finding(s) in Supply-chain Provenance & Signing. — One of this dimension's main actionable groups (1 recommendation-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 0 platform declaration(s) and 38 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 composition7.1 / 10Strong✓ 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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AX5 · Architecture & structure10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.

Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.

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M1 · Documentation (README)6.0 / 10Adequate✓ 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.

What to do

Add a build/run (quick start) section to the root README — the first thing a newcomer needs.
Add a 'Testing' section to the root README — how to run the test suite.
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 1 of 1 project(s) that lack one — worth up to 2 pts.

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M2 · Architecture documentation5.0 / 10Adequate✓ 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.

No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.

What to do

Record significant decisions one document per decision — dated, stating the context, the decision and its consequences — and keep them together wherever your design docs already live (a conventional `docs/adr/` tree, with each file named `NNNN-title` in whatever markup those docs already use, is the most discoverable form).

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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◐ Sampled · advisory

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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P2 · Observability10.0 / 10Exemplary○ Nothing flagged

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.

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P3 · Security & performance tooling0.0 / 10Critical✓ 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.

No static application security testing detected. For this repository's stack, add scalafix or scapegoat (or `semgrep --config=auto`, which runs on any language) as a CI step. What was searched, so you can tell an absence from a miss: the 16221 CI workflow file(s) in this repository, and the scanner and linter configuration checked in beside them. A scan that runs outside CI, one configured in your forge's web UI rather than in a committed file, or a tool whose name is none of those this check carries, is not seen — if that is your case the row is wrong, and saying so is more useful than adding a second scanner.

What to do

Add a SAST step to CI running what this repository's stack ships: scalafix or scapegoat — or `semgrep --config=auto`, which runs on any language — so a security regression fails the build instead of landing.
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 & Rollback5.0 / 10Adequate✓ 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.
Add an approval/environment gate (required reviewers / protection rules) before production promotion.

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P5 · DR & Backup0.0 / 10Critical✓ 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.

A persistence guard (data volume / purge-protection) was found, but no backup, geo-recovery or RTO/RPO controls were evidenced — a volume that survives a container recreate is not a tested restore from catastrophic loss.

What to do

Codify backups + geo-recovery in IaC and document RTO/RPO and the restore procedure — a persistence guard alone is not disaster recovery.

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P6 · Release Hygiene5.0 / 10Adequate✓ 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.

No CHANGELOG/HISTORY/RELEASES file — what shipped when isn't easy to reconstruct for support or audit. (Versioning/tagging makes releases traceable, but a changelog records the what.)

What to do

Keep a changelog (e.g. Keep-a-Changelog) recording what shipped in each release.

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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	85%	Strong	Strongest area.
Architecture	76%	Adequate — gated by D26	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Maturity	70%	Strong	Solid.
Readiness	39%	Weak — gated by P3, P5	Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Security	62%	Adequate — gated by D29, D31, D36	Capped at Fair by a Critical contributor — resolve it before relying on this lens.

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 — 80 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 analysed — these correctness checks read a source model 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
AX2 Stateful singletons — not analysed — these correctness checks read a source model 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
AX3 Project dependency cycles — not assessed — project cycles and dependency direction are computed over a project-reference graph that was not loaded for this repository, because the repository commits no project file of a kind this check models. This is a gap in the analyzer, not a finding about this repository
AX4 Dependency direction — not applicable to a CQRS architecture (the inward-dependency rule is for layered/clean styles)
AX6 Interface segregation — not assessed — interface segregation is computed over a type surface 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 — not assessed — test isolation is computed from a project graph (which projects are test projects, and what they reference) that was not loaded for this repository, because the repository commits no project file of a kind this check models. This is a gap in the analyzer, not a finding about this repository
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) — mongodb Pulling zookeeper Pulling main Pulling kafka Pulling main Error Get "https://registry-1.docker.io/v2/": Forbidden mongodb Error context canceled zookeeper Error context canceled kafka Error context canceled Error response from daemon: Get "https://registry-1.docker.io/v2/": Forbidden; the earlier `compose pull` step reported: zookeeper Pulling kafka Pulling main Pulling mongodb Pulling zookeeper Error Get "https://registry-1.docker.io/v2/": Forbidden kafka Error context canceled mongodb Error context canceled main Error context canceled 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 — ~28881 lines of test source are present (.scala, .py) 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 — the .scala suite was found but not re-run
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.
D22 Internal API Consistency — The exposed public-API surface could not be collected — no C#/VB projects loaded.
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. 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 — No inline comments to assess — comment value is not applicable here.
D25 ADR Conformance — no ADRs to check
D27 Navigability — symbol resolution incomplete — navigability not assessed
D32 Data Compliance (PII/GDPR) — 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.
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.
D5 Coupling — D5 reads a .NET project-reference graph only — this repository's production source is .java, .py, .scala, which was left unread. Not scored: this is a gap in the analyzer, not a verdict about this repository.
D7 Architectural Integrity — no checkable ADRs, and no project-reference graph for the cycle pass to read — so this dimension makes no claim about dependency cycles in either direction (where this repository's language has an import-cycle lens, cycles are reported there). Architectural integrity not assessed
D8 Code Coverage — Coverage not included — suite not readable by the collector
DM1 Domain Modelling — applicable but not scored (1 of 2 signals for this style — below the bar we score at): 121 value object(s)
ED1 Event-Driven — not scored — this repository shows only 1 of the 3 signals this lens looks for (1 CQRS handler(s))
ED5 Idempotency — This check finds retry-prone mutations (command handlers and message/event consumers) by walking the repository's declared types, and none was loaded here, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this lens looks for
GD1 Unfinished & placeholder code — no source files were read — this check reads C# syntax, and none was loaded for this repository. That is a limit of the analyzer, not a finding about your code.
IC1 Incompleteness & stubs — not analysed — these correctness checks read a source model 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
P10 Library API & versioning — not analysed — these correctness checks read a source model 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
P12 CI test-gate honesty — Reported, not scored — and nothing was matched here. The coverage check applies to any stack, and the automatic-re-run check to any GitHub-Actions workflow, but the checks for excluded tests, skipped tests and sleep-based synchronisation currently recognise only some ecosystems' test-runner idioms, so on a repository built with another stack the zeros below mean 'not checked', not 'clean'.
P7 Outbound HTTP resilience — not applicable — no HTTP server, API framework or worker entry point was found in the JVM, 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
PF1 Benchmark discipline — not analysed — these correctness checks read a source model 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
PF2 Allocation hygiene — not analysed — these correctness checks read a source model 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
PF3 Async & latency hygiene — Sync-over-async was not assessed: this repository's async code is written in Scala, whose blocking calls this check does not model yet. That is a gap in the analyzer's language reach, not a finding about your code.
S1 Web-Security Posture — Not assessed: these web-security 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 web-security 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.
X1 Async correctness — not analysed — these correctness checks read a source model 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
X10 Duplicated predicate — not analysed — these correctness checks read a source model 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
X12 Unreachable branch — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X13 Undrained process stream — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X14 Bypassable address classification — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X15 Unvalidated length from an untrusted reader — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X16 Unfloored truncation loop — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X17 Uncapped recursion over a caller-supplied document — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X18 Disposal-pattern correctness — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X19 Unrestored process-global state — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X2 Cancellation propagation — not analysed — these correctness checks read a source model 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
X20 Mistyped argument guard — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X21 Side-effecting pattern guard — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X22 Contradicted release guard — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X23 Unguarded diagnostic materialisation — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X24 Document value interpolated into markup unescaped — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X25 Inert configuration knob — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X26 Unsynchronised callback handoff — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X27 Collection changed while being enumerated — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X28 Index access outside its own emptiness guard — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X29 Per-element action decided by a fixed element — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X3 Exception handling — not analysed — these correctness checks read a source model 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
X30 Support guard that admits what it rejects — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X32 Type resolved by simple name across every loaded assembly — This check reads C# syntax; no C# was loaded for this repository, so it has nothing to report. That is a limit of the analyzer, not a finding about your code.
X4 Structured logging — not analysed — these correctness checks read a source model 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
X5 Nullable reference types — not analysed — these correctness checks read a source model 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
X6 Hand-rolled structured-format parsing — not analysed — these correctness checks read a source model 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
X7 Silent fallback defaults — not analysed — these correctness checks read a source model 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
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 — 42 finding(s)

D31 · IaC & Container Security · High IaC · ×17

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D29 · Static Analysis (SAST) · REDACTED

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D30 · Dependency Vulnerabilities · High CVE · ×4

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D29 · Static Analysis (SAST) · REDACTED

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Serious — 180 finding(s)

D17 · Explicit Debt · TodoComment · ×51

TodoComment aggregator/src/main/scala/ai/chronon/aggregator/base/TimedAggregators.scala:139 — // TODO: tuple making is unnecessary if we are not going to 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 aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:160 — // TODO this might need more type handling — 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 aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:190 — // TODO: remove the below assertion and add support — 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 aggregator/src/main/scala/ai/chronon/aggregator/windowing/SawtoothOnlineAggregator.scala:79 — // TODO: We can cache aggregated values in a very interesting way — 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 aggregator/src/main/scala/ai/chronon/aggregator/windowing/SawtoothOnlineAggregator.scala:166 — // TODO: Add support for mutations / hasReversal to the tiled implementation — 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 aggregator/src/test/scala/ai/chronon/aggregator/test/SawtoothAggregatorTest.scala:40 — // TODO: Write this out into a file checked into git — 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 api/py/ai/chronon/join.py:114 — # TODO: custom_json can take privacy information per column, we can propagate — 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 api/py/ai/chronon/join.py:542 — # # TODO: Add back validation? Or not? — 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 api/py/ai/chronon/group_by.py:227 — # TODO undo this check after ml_models CI passes — 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 api/py/ai/chronon/repo/dependency_tracker.py:75 — # TODO: Implement the downstream check for staging queries — 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 api/py/ai/chronon/repo/__init__.py:17 — # TODO - make team part of thrift API? — 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 api/py/test/sample/scripts/yarn_list.py:37 — # TODO: REPLACE WITH path to your YARN — 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 api/py/test/sample/scripts/yarn_list.py:40 — # TODO: REPLACE WITH path to your cluster confs — 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 api/py/test/sample/scripts/fetch_online_jar.py:3 — # TODO: Implement how to fetch your jar for online implementation of ai.chronon.online.Api interface/trait — 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 api/src/main/scala/ai/chronon/api/Extensions.scala:640 — //todo: this logic is similar in JoinSourceRunner, we can simplify it to a single place — 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 api/src/main/scala/ai/chronon/api/Extensions.scala:981 — // TODO: validate that non keys are not specified in - join.skewKeys — 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 api/src/main/scala/ai/chronon/api/Extensions.scala:1090 — // TODO: supports opt-out in the future — 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 flink/src/main/scala/ai/chronon/flink/SparkExpressionEvalFn.scala:61 — // TODO handle UDFs — 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 flink/src/main/scala/ai/chronon/flink/AvroCodecFn.scala:36 — // TODO: update to use constant names that are company specific — 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 online/src/main/java/ai/chronon/online/JavaExternalSourceHandler.java:40 — // TODO: deprecate ScalaVersionSpecificCollectionsConverter in java — 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 online/src/main/scala/ai/chronon/online/FetcherBase.scala:394 — // TODO: only gets hit in cli path - make this code path just use avro schema to decode keys directly in cli — 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 online/src/main/scala/ai/chronon/online/FetcherBase.scala:395 — // TODO: Remove this code block — 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 online/src/main/scala/ai/chronon/online/ExternalSourceRegistry.scala:108 — // TODO: validation of externally fetched data — 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 online/src/main/scala/ai/chronon/online/DataStreamBuilder.scala:69 — // TODO: Explore whether timeColumn for entities can be dropped in life-time aggregate cases — 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 online/src/main/scala/ai/chronon/online/CatalystUtil.scala:154 — // TODO: Generalize this beyond fetching join derivations. — 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.
+ 26 more in this group — see findings.md.

D3 · God Classes · FileTooLong · ×11

FileTooLong: spark/Driver.scala spark/src/main/scala/ai/chronon/spark/Driver.scala — FileTooLong — 895 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 395 over it, 1.79× 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: api/Extensions.scala api/src/main/scala/ai/chronon/api/Extensions.scala — FileTooLong — 830 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 330 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: REDACTED REDACTED — FileTooLong — 801 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 301 over it, 1.60× 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: spark/GroupBy.scala spark/src/main/scala/ai/chronon/spark/GroupBy.scala — FileTooLong — 770 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 270 over it, 1.54× 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: spark/Analyzer.scala spark/src/main/scala/ai/chronon/spark/Analyzer.scala — FileTooLong — 724 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 224 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: online/Fetcher.scala online/src/main/scala/ai/chronon/online/Fetcher.scala — FileTooLong — 616 significant lines (blank, comment-only and punctuation-only lines excluded), about 90% of them inside a single declaration: Fetcher (93-860). The bar is 500 significant lines; this is 116 over it, 1.23× 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: base/SimpleAggregators.scala aggregator/src/main/scala/ai/chronon/aggregator/base/SimpleAggregators.scala — FileTooLong — 605 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 105 over it, 1.21× 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: streaming/JoinSourceRunner.scala spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala — FileTooLong — 587 significant lines (blank, comment-only and punctuation-only lines excluded), about 92% of them inside a single declaration: JoinSourceRunner (91-906). The bar is 500 significant lines; this is 87 over it, 1.17× 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: online/FetcherBase.scala online/src/main/scala/ai/chronon/online/FetcherBase.scala — FileTooLong — 579 significant lines (blank, comment-only and punctuation-only lines excluded), about 96% of them inside a single declaration: FetcherBase (43-832). The bar is 500 significant lines; this is 79 over it, 1.16× 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: repo/compile.py api/py/ai/chronon/repo/compile.py — FileTooLong — 531 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 31 over it, 1.06× 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 — 513 significant lines (blank, comment-only and punctuation-only lines excluded). The bar is 500 significant lines; this is 13 over it, 1.03× 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.

D31 · IaC & Container Security · Medium IaC · ×11

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D6 · Cohesion (LCOM4) · Low cohesion · ×6

Low cohesion: SourceOps (LCOM4 8) api/src/main/scala/ai/chronon/api/Extensions.scala:312 — SourceOps's methods fall into 8 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 8 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: GroupByOps (LCOM4 8) api/src/main/scala/ai/chronon/api/Extensions.scala:446 — GroupByOps's methods fall into 8 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 8 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: FrequentItems (LCOM4 6) aggregator/src/main/scala/ai/chronon/aggregator/base/SimpleAggregators.scala:376 — FrequentItems's methods fall into 6 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 6 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: DataframeOps (LCOM4 6) REDACTED:96 — DataframeOps's methods fall into 6 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 6 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: OrderByLimitTimed (LCOM4 4) aggregator/src/main/scala/ai/chronon/aggregator/base/TimedAggregators.scala:117 — OrderByLimitTimed'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: Fetcher (LCOM4 4) online/src/main/scala/ai/chronon/online/Fetcher.scala:93 — Fetcher'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.

D30 · Dependency Vulnerabilities · Medium CVE · ×5

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D4 · Code Duplication · Duplicated block (9 lines × 2) · ×3

Duplicated block (9 lines × 2) flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:91 — flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:91-99 | flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:142-150 — 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. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just before the matched lines, `flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:140` calls `getSmallestWindowResolutionInMillis` and `flink/src/main/scala/ai/chronon/flink/FlinkJob.scala:89` 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 (9 lines × 2) online/src/main/scala/ai/chronon/online/CatalystUtil.scala:224 — online/src/main/scala/ai/chronon/online/CatalystUtil.scala:224-232 | online/src/main/scala/ai/chronon/online/CatalystUtil.scala:257-265 — 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 `online/src/main/scala/ai/chronon/online/CatalystUtil.scala: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 (9 lines × 2) api/py/ai/chronon/lineage/lineage_parser.py:206 — api/py/ai/chronon/lineage/lineage_parser.py:206-214 | api/py/ai/chronon/lineage/lineage_parser.py:242-250 — 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. 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 (5 lines × 2) · ×3

Duplicated block (5 lines × 2) spark/src/main/scala/ai/chronon/spark/GroupBy.scala:821 — spark/src/main/scala/ai/chronon/spark/GroupBy.scala:821-825 | spark/src/main/scala/ai/chronon/spark/GroupBy.scala:1027-1034 — 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) spark/src/main/scala/ai/chronon/spark/JoinBase.scala:547 — spark/src/main/scala/ai/chronon/spark/JoinBase.scala:547-551 | spark/src/main/scala/ai/chronon/spark/JoinBase.scala:591-595 — 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/ai/chronon/spark/JoinBase.scala:547` 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/src/main/scala/ai/chronon/spark/Analyzer.scala:287 — spark/src/main/scala/ai/chronon/spark/Analyzer.scala:287-291 | spark/src/main/scala/ai/chronon/spark/BootstrapInfo.scala:111-115 — 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/ai/chronon/spark/Analyzer.scala:287` 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.

D3 · God Classes · ClassTooLong · ×2

ClassTooLong: JoinSourceRunner spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:91 — ClassTooLong — 539 significant lines (blank, comment-only and punctuation-only lines excluded), 18 methods. The bar is 400 significant lines; this is 139 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: JoinBase spark/src/main/scala/ai/chronon/spark/JoinBase.scala:39 — ClassTooLong — 476 significant lines (blank, comment-only and punctuation-only lines excluded), 14 methods. The bar is 400 significant lines; this is 76 over it, 1.19× 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.

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

Duplicated block (10 lines × 2) online/src/main/scala/ai/chronon/online/FetcherBase.scala:151 — online/src/main/scala/ai/chronon/online/FetcherBase.scala:151-160 | online/src/main/scala/ai/chronon/online/FetcherBase.scala:199-208 — 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 `online/src/main/scala/ai/chronon/online/FetcherBase.scala:151` 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) airflow/group_by_dag_constructor.py:8 — airflow/group_by_dag_constructor.py:8-18 | airflow/staging_query_dag_constructor.py:10-19 — 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 (8 lines × 2) · ×2

Duplicated block (8 lines × 2) quickstart/mongo-online-impl/src/main/scala/ai/chronon/quickstart/online/QuickstartMutationDecoder.scala:47 — quickstart/mongo-online-impl/src/main/scala/ai/chronon/quickstart/online/QuickstartMutationDecoder.scala:47-54 | quickstart/mongo-online-impl/src/main/scala/ai/chronon/quickstart/online/QuickstartMutationDecoder.scala:79-86 — 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 `quickstart/mongo-online-impl/src/main/scala/ai/chronon/quickstart/online/QuickstartMutationDecoder.scala:47` 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 (8 lines × 2) api/py/ai/chronon/repo/compile.py:676 — api/py/ai/chronon/repo/compile.py:676-683 | api/py/ai/chronon/repo/compile.py:693-700 — 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. ★ These copies have DRIFTED, and that is worth reading before extracting anything: just after the matched lines, `api/py/ai/chronon/repo/compile.py:702` calls `_preserve_mode_to_env_map` and `api/py/ai/chronon/repo/compile.py:684` 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 (7 lines × 2) · ×2

Duplicated block (7 lines × 2) api/src/main/scala/ai/chronon/api/Extensions.scala:624 — api/src/main/scala/ai/chronon/api/Extensions.scala:624-630 | spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:60-66 — 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.
Duplicated block (7 lines × 2) spark/src/main/scala/ai/chronon/spark/JoinBase.scala:540 — spark/src/main/scala/ai/chronon/spark/JoinBase.scala:540-546 | spark/src/main/scala/ai/chronon/spark/JoinBase.scala:584-590 — 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/ai/chronon/spark/JoinBase.scala:540` 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.

D1 · Cyclomatic Complexity · ColumnAggregator.construct (cyclomatic 106) · ×1

ColumnAggregator.construct (cyclomatic 106) aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:227 — ColumnAggregator.construct has cyclomatic complexity 106 (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 · group_by.validate_group_by (cyclomatic 33) · ×1

group_by.validate_group_by (cyclomatic 33) api/py/ai/chronon/group_by.py:221 — group_by.validate_group_by has cyclomatic complexity 33 (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 · SparkInternalRowConversions.to (cyclomatic 26) · ×1

SparkInternalRowConversions.to (cyclomatic 26) online/src/main/scala/ai/chronon/online/SparkInternalRowConversions.scala:130 — SparkInternalRowConversions.to 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 · Row.to (cyclomatic 25) · ×1

Row.to (cyclomatic 25) api/src/main/scala/ai/chronon/api/Row.scala:130 — Row.to has cyclomatic complexity 25 (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 · FetcherBase.fetchGroupBys (cyclomatic 24) · ×1

FetcherBase.fetchGroupBys (cyclomatic 24) online/src/main/scala/ai/chronon/online/FetcherBase.scala:353 — FetcherBase.fetchGroupBys has cyclomatic complexity 24 (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 · FastHashing.generateKeyBuilder (cyclomatic 24) · ×1

FastHashing.generateKeyBuilder (cyclomatic 24) spark/src/main/scala/ai/chronon/spark/FastHashing.scala:48 — FastHashing.generateKeyBuilder has cyclomatic complexity 24 (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 · compile.extract_and_convert (cyclomatic 24) · ×1

compile.extract_and_convert (cyclomatic 24) api/py/ai/chronon/repo/compile.py:90 — compile.extract_and_convert 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 · run.set_runtime_env (cyclomatic 24) · ×1

run.set_runtime_env (cyclomatic 24) REDACTED:239 — run.set_runtime_env 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 · FetcherBase.constructGroupByResponse (cyclomatic 21) · ×1

FetcherBase.constructGroupByResponse (cyclomatic 21) online/src/main/scala/ai/chronon/online/FetcherBase.scala:59 — FetcherBase.constructGroupByResponse 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 · Analyzer.analyzeJoin (cyclomatic 21) · ×1

Analyzer.analyzeJoin (cyclomatic 21) spark/src/main/scala/ai/chronon/spark/Analyzer.scala:343 — Analyzer.analyzeJoin 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 · LineageParser.parse_join (cyclomatic 21) · ×1

LineageParser.parse_join (cyclomatic 21) api/py/ai/chronon/lineage/lineage_parser.py:429 — LineageParser.parse_join 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 · Fetcher.logResponseInternal (cyclomatic 20) · ×1

Fetcher.logResponseInternal (cyclomatic 20) online/src/main/scala/ai/chronon/online/Fetcher.scala:498 — Fetcher.logResponseInternal 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 · Runner.run (cyclomatic 19) · ×1

Runner.run (cyclomatic 19) REDACTED:411 — Runner.run 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 · utils.get_modes_tables (cyclomatic 19) · ×1

utils.get_modes_tables (cyclomatic 19) api/py/ai/chronon/utils.py:473 — utils.get_modes_tables 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 · join.Join (cyclomatic 18) · ×1

join.Join (cyclomatic 18) api/py/ai/chronon/join.py:392 — join.Join 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 · PlatformInterface.set_metadata (cyclomatic 18) · ×1

PlatformInterface.set_metadata (cyclomatic 18) api/py/ai/chronon/pyspark/executables.py:839 — PlatformInterface.set_metadata 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 · FetcherBase.fetchJoin (cyclomatic 17) · ×1

FetcherBase.fetchJoin (cyclomatic 17) online/src/main/scala/ai/chronon/online/FetcherBase.scala:611 — FetcherBase.fetchJoin 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 · TwoStackLiteAggregator.slidingSawtoothWindow (cyclomatic 16) · ×1

TwoStackLiteAggregator.slidingSawtoothWindow (cyclomatic 16) aggregator/src/main/scala/ai/chronon/aggregator/windowing/TwoStackLiteAggregator.scala:66 — TwoStackLiteAggregator.slidingSawtoothWindow 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 · Analyzer.runDataAvailabilityCheck (cyclomatic 16) · ×1

Analyzer.runDataAvailabilityCheck (cyclomatic 16) spark/src/main/scala/ai/chronon/spark/Analyzer.scala:641 — Analyzer.runDataAvailabilityCheck 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 · JoinSourceRunner.enrichBaseJoin (cyclomatic 16) · ×1

JoinSourceRunner.enrichBaseJoin (cyclomatic 16) spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:494 — JoinSourceRunner.enrichBaseJoin 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 · LineageParser.parse_join (cognitive 56) · ×1

LineageParser.parse_join (cognitive 56) api/py/ai/chronon/lineage/lineage_parser.py:429 — LineageParser.parse_join has cognitive complexity 56 (threshold 15). Drivers by points: if/else 15 (40 pts), loops 5 (8 pts), error handling 1 (5 pts), ternaries 1 (2 pts), boolean chains 1 (nesting depth added 33). 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 · group_by.validate_group_by (cognitive 52) · ×1

group_by.validate_group_by (cognitive 52) api/py/ai/chronon/group_by.py:221 — group_by.validate_group_by has cognitive complexity 52 (threshold 15). Drivers by points: if/else 13 (24 pts), boolean chains 13, ternaries 3 (6 pts), error handling 1 (5 pts), loops 3 (4 pts) (nesting depth added 19). 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 · ColumnAggregator.construct (cognitive 49) · ×1

ColumnAggregator.construct (cognitive 49) aggregator/src/main/scala/ai/chronon/aggregator/row/ColumnAggregator.scala:227 — ColumnAggregator.construct has cognitive complexity 49 (threshold 15). Drivers by points: match/switch 18 (32 pts), if/else 17 (nesting depth added 14). 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 · run.set_runtime_env (cognitive 48) · ×1

run.set_runtime_env (cognitive 48) REDACTED:239 — run.set_runtime_env has cognitive complexity 48 (threshold 15). Drivers by points: if/else 13 (33 pts), boolean chains 5, error handling 1 (4 pts), loops 3 (4 pts), ternaries 1 (2 pts) (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 · compile.extract_and_convert (cognitive 43) · ×1

compile.extract_and_convert (cognitive 43) api/py/ai/chronon/repo/compile.py:90 — compile.extract_and_convert has cognitive complexity 43 (threshold 15). Drivers by points: if/else 18 (33 pts), loops 3 (7 pts), boolean chains 3 (nesting depth added 19). 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 · FetcherBase.constructGroupByResponse (cognitive 40) · ×1

FetcherBase.constructGroupByResponse (cognitive 40) online/src/main/scala/ai/chronon/online/FetcherBase.scala:59 — FetcherBase.constructGroupByResponse has cognitive complexity 40 (threshold 15). Drivers by points: if/else 14 (28 pts), match/switch 4 (10 pts), boolean chains 2 (nesting depth added 20). 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 · Fetcher.logResponseInternal (cognitive 34) · ×1

Fetcher.logResponseInternal (cognitive 34) online/src/main/scala/ai/chronon/online/Fetcher.scala:498 — Fetcher.logResponseInternal has cognitive complexity 34 (threshold 15). Drivers by points: if/else 20 (28 pts), boolean chains 3, 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 · SparkInternalRowConversions.to (cognitive 34) · ×1

SparkInternalRowConversions.to (cognitive 34) online/src/main/scala/ai/chronon/online/SparkInternalRowConversions.scala:130 — SparkInternalRowConversions.to has cognitive complexity 34 (threshold 15). Drivers by points: if/else 17 (27 pts), match/switch 4 (7 pts) (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 · LineageParser.parse_group_by (cognitive 34) · ×1

LineageParser.parse_group_by (cognitive 34) api/py/ai/chronon/lineage/lineage_parser.py:625 — LineageParser.parse_group_by has cognitive complexity 34 (threshold 15). Drivers by points: if/else 11 (22 pts), loops 5 (11 pts), boolean chains 1 (nesting depth added 17). 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 · Analyzer.analyzeJoin (cognitive 33) · ×1

Analyzer.analyzeJoin (cognitive 33) spark/src/main/scala/ai/chronon/spark/Analyzer.scala:343 — Analyzer.analyzeJoin has cognitive complexity 33 (threshold 15). Drivers by points: if/else 25 (28 pts), boolean chains 4, match/switch 1 (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 · LineageParser.build_join_sql (cognitive 33) · ×1

LineageParser.build_join_sql (cognitive 33) api/py/ai/chronon/lineage/lineage_parser.py:340 — LineageParser.build_join_sql has cognitive complexity 33 (threshold 15). Drivers by points: if/else 7 (21 pts), loops 5 (10 pts), ternaries 1 (2 pts) (nesting depth added 20). 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 · Analyzer.runDataAvailabilityCheck (cognitive 32) · ×1

Analyzer.runDataAvailabilityCheck (cognitive 32) spark/src/main/scala/ai/chronon/spark/Analyzer.scala:641 — Analyzer.runDataAvailabilityCheck has cognitive complexity 32 (threshold 15). Drivers by points: if/else 12 (26 pts), match/switch 2 (5 pts), boolean chains 1 (nesting depth added 17). 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 · FetcherBase.fetchGroupBys (cognitive 31) · ×1

FetcherBase.fetchGroupBys (cognitive 31) online/src/main/scala/ai/chronon/online/FetcherBase.scala:353 — FetcherBase.fetchGroupBys has cognitive complexity 31 (threshold 15). Drivers by points: match/switch 8 (13 pts), if/else 10 (11 pts), error handling 4 (5 pts), boolean chains 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 · helpers.walk_and_define_tasks (cognitive 30) · ×1

helpers.walk_and_define_tasks (cognitive 30) airflow/helpers.py:315 — helpers.walk_and_define_tasks has cognitive complexity 30 (threshold 15). Drivers by points: if/else 6 (20 pts), error handling 2 (6 pts), loops 2 (3 pts), boolean chains 1 (nesting depth added 19). 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 · PlatformInterface.set_metadata (cognitive 28) · ×1

PlatformInterface.set_metadata (cognitive 28) api/py/ai/chronon/pyspark/executables.py:839 — PlatformInterface.set_metadata has cognitive complexity 28 (threshold 15). Drivers by points: if/else 7 (13 pts), loops 4 (10 pts), boolean chains 3, error handling 1 (2 pts) (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 · utils.get_modes_tables (cognitive 28) · ×1

utils.get_modes_tables (cognitive 28) api/py/ai/chronon/utils.py:473 — utils.get_modes_tables has cognitive complexity 28 (threshold 15). Drivers by points: if/else 13 (23 pts), boolean chains 5 (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 · Runner.run (cognitive 27) · ×1

Runner.run (cognitive 27) REDACTED:411 — Runner.run has cognitive complexity 27 (threshold 15). Drivers by points: if/else 7 (13 pts), error handling 2 (5 pts), loops 2 (4 pts), boolean chains 3, ternaries 1 (2 pts) (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 · TwoStackLiteAggregator.slidingSawtoothWindow (cognitive 26) · ×1

TwoStackLiteAggregator.slidingSawtoothWindow (cognitive 26) aggregator/src/main/scala/ai/chronon/aggregator/windowing/TwoStackLiteAggregator.scala:66 — TwoStackLiteAggregator.slidingSawtoothWindow has cognitive complexity 26 (threshold 15). Drivers by points: if/else 9 (13 pts), loops 7 (11 pts), boolean chains 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 · FastHashing.generateKeyBuilder (cognitive 26) · ×1

FastHashing.generateKeyBuilder (cognitive 26) spark/src/main/scala/ai/chronon/spark/FastHashing.scala:48 — FastHashing.generateKeyBuilder has cognitive complexity 26 (threshold 15). Drivers by points: match/switch 11 (21 pts), if/else 2 (3 pts), loops 2 (nesting depth added 11). 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 · SawtoothAggregator.cumulate (cognitive 24) · ×1

SawtoothAggregator.cumulate (cognitive 24) aggregator/src/main/scala/ai/chronon/aggregator/windowing/SawtoothAggregator.scala:97 — SawtoothAggregator.cumulate has cognitive complexity 24 (threshold 15). Drivers by points: if/else 7 (12 pts), loops 4 (8 pts), boolean chains 4 (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 · TableUtils.repartitionAndWriteInternal (cognitive 24) · ×1

TableUtils.repartitionAndWriteInternal (cognitive 24) REDACTED:726 — TableUtils.repartitionAndWriteInternal has cognitive complexity 24 (threshold 15). Drivers by points: if/else 16 (22 pts), boolean chains 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 · EditDistance.between (cognitive 24) · ×1

EditDistance.between (cognitive 24) spark/src/main/scala/ai/chronon/spark/stats/EditDistance.scala:54 — EditDistance.between has cognitive complexity 24 (threshold 15). Drivers by points: if/else 12 (17 pts), loops 3 (4 pts), boolean chains 3 (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 · JoinBase.computeJoinOpt (cognitive 23) · ×1

JoinBase.computeJoinOpt (cognitive 23) spark/src/main/scala/ai/chronon/spark/JoinBase.scala:609 — JoinBase.computeJoinOpt has cognitive complexity 23 (threshold 15). Drivers by points: if/else 15 (19 pts), error handling 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 · JoinSourceRunner.enrichBaseJoin (cognitive 23) · ×1

JoinSourceRunner.enrichBaseJoin (cognitive 23) spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:494 — JoinSourceRunner.enrichBaseJoin has cognitive complexity 23 (threshold 15). Drivers by points: if/else 10 (12 pts), error handling 3 (7 pts), boolean chains 4 (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 · join.Join (cognitive 23) · ×1

join.Join (cognitive 23) api/py/ai/chronon/join.py:392 — join.Join has cognitive complexity 23 (threshold 15). Drivers by points: if/else 8 (11 pts), ternaries 3 (5 pts), boolean chains 4, loops 2 (3 pts) (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 · ChrononRepoValidator._validate_derivations (cognitive 22) · ×1

ChrononRepoValidator._validate_derivations (cognitive 22) api/py/ai/chronon/repo/validator.py:348 — ChrononRepoValidator._validate_derivations has cognitive complexity 22 (threshold 15). Drivers by points: if/else 8 (19 pts), boolean chains 2, loops 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 · BootstrapInfo.from (cognitive 21) · ×1

BootstrapInfo.from (cognitive 21) spark/src/main/scala/ai/chronon/spark/BootstrapInfo.scala:78 — BootstrapInfo.from has cognitive complexity 21 (threshold 15). Drivers by points: if/else 14 (15 pts), boolean chains 3, loops 2 (3 pts) (nesting depth added 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 · helpers.should_schedule (cognitive 21) · ×1

helpers.should_schedule (cognitive 21) airflow/helpers.py:116 — helpers.should_schedule has cognitive complexity 21 (threshold 15). Drivers by points: if/else 11 (19 pts), boolean chains 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 · helpers.task_names (cognitive 21) · ×1

helpers.task_names (cognitive 21) airflow/helpers.py:284 — helpers.task_names has cognitive complexity 21 (threshold 15). Drivers by points: if/else 12 (20 pts), boolean chains 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 · TBaseDecoderFactory.build (cognitive 20) · ×1

TBaseDecoderFactory.build (cognitive 20) online/src/main/java/ai/chronon/online/TBaseDecoderFactory.java:57 — TBaseDecoderFactory.build has cognitive complexity 20 (threshold 15). Drivers by points: if/else 15 (20 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 · helpers.dag_names (cognitive 20) · ×1

helpers.dag_names (cognitive 20) airflow/helpers.py:253 — helpers.dag_names has cognitive complexity 20 (threshold 15). Drivers by points: if/else 12 (19 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 · Row.from (cognitive 18) · ×1

Row.from (cognitive 18) api/src/main/scala/ai/chronon/api/Row.scala:75 — Row.from has cognitive complexity 18 (threshold 15). Drivers by points: loops 3 (9 pts), match/switch 4 (7 pts), if/else 2 (nesting depth added 9). 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 · FetcherCli.run (cognitive 18) · ×1

FetcherCli.run (cognitive 18) spark/src/main/scala/ai/chronon/spark/Driver.scala:810 — FetcherCli.run has cognitive complexity 18 (threshold 15). Drivers by points: if/else 10 (13 pts), boolean chains 2, match/switch 1 (2 pts), loops 1 (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 · SawtoothMutationAggregator.mergeTailHops (cognitive 17) · ×1

SawtoothMutationAggregator.mergeTailHops (cognitive 17) aggregator/src/main/scala/ai/chronon/aggregator/windowing/SawtoothMutationAggregator.scala:147 — SawtoothMutationAggregator.mergeTailHops has cognitive complexity 17 (threshold 15). Drivers by points: if/else 4 (12 pts), loops 2 (4 pts), boolean chains 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 · FetcherBase.fetchJoin (cognitive 17) · ×1

FetcherBase.fetchJoin (cognitive 17) online/src/main/scala/ai/chronon/online/FetcherBase.scala:611 — FetcherBase.fetchJoin has cognitive complexity 17 (threshold 15). Drivers by points: if/else 7 (9 pts), match/switch 5 (7 pts), boolean chains 1 (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 · Analyzer.analyzeGroupBy (cognitive 17) · ×1

Analyzer.analyzeGroupBy (cognitive 17) spark/src/main/scala/ai/chronon/spark/Analyzer.scala:241 — Analyzer.analyzeGroupBy has cognitive complexity 17 (threshold 15). Drivers by points: if/else 14 (16 pts), boolean chains 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 · GroupBy.computeBackfill (cognitive 17) · ×1

GroupBy.computeBackfill (cognitive 17) spark/src/main/scala/ai/chronon/spark/GroupBy.scala:989 — GroupBy.computeBackfill has cognitive complexity 17 (threshold 15). Drivers by points: if/else 10, boolean chains 4, match/switch 2, error handling 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 · Join.computeRange (cognitive 17) · ×1

Join.computeRange (cognitive 17) spark/src/main/scala/ai/chronon/spark/Join.scala:264 — Join.computeRange has cognitive complexity 17 (threshold 15). Drivers by points: if/else 10 (11 pts), boolean chains 5, error handling 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 · PySparkExecutable._execute_underlying_join_sources (cognitive 17) · ×1

PySparkExecutable._execute_underlying_join_sources (cognitive 17) api/py/ai/chronon/pyspark/executables.py:103 — PySparkExecutable._execute_underlying_join_sources has cognitive complexity 17 (threshold 15). Drivers by points: if/else 6 (12 pts), loops 3 (4 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 · explore.enrich_with_joins (cognitive 17) · ×1

explore.enrich_with_joins (cognitive 17) REDACTED:267 — explore.enrich_with_joins has cognitive complexity 17 (threshold 15). Drivers by points: if/else 3 (10 pts), loops 5 (7 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 · DerivationUtils.applyDerivation (cognitive 16) · ×1

DerivationUtils.applyDerivation (cognitive 16) online/src/main/scala/ai/chronon/online/DerivationUtils.scala:130 — DerivationUtils.applyDerivation has cognitive complexity 16 (threshold 15). Drivers by points: if/else 12 (14 pts), boolean chains 2 (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 · Fetcher.fetchDerivations (cognitive 16) · ×1

Fetcher.fetchDerivations (cognitive 16) online/src/main/scala/ai/chronon/online/Fetcher.scala:334 — Fetcher.fetchDerivations has cognitive complexity 16 (threshold 15). Drivers by points: if/else 6 (9 pts), match/switch 3 (6 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 · JoinSourceRunner.writeToKVStore (cognitive 16) · ×1

JoinSourceRunner.writeToKVStore (cognitive 16) spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:725 — JoinSourceRunner.writeToKVStore has cognitive complexity 16 (threshold 15). Drivers by points: if/else 9 (12 pts), match/switch 2 (4 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 · LineageParser.get_join_key_columns (cognitive 16) · ×1

LineageParser.get_join_key_columns (cognitive 16) api/py/ai/chronon/lineage/lineage_parser.py:410 — LineageParser.get_join_key_columns has cognitive complexity 16 (threshold 15). Drivers by points: if/else 3 (9 pts), loops 3 (7 pts) (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 · explore.prettify_entry (cognitive 16) · ×1

explore.prettify_entry (cognitive 16) REDACTED:220 — explore.prettify_entry has cognitive complexity 16 (threshold 15). Drivers by points: if/else 6 (12 pts), loops 2 (3 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 · extract_objects.import_module_set_name (cognitive 16) · ×1

extract_objects.import_module_set_name (cognitive 16) api/py/ai/chronon/repo/extract_objects.py:44 — extract_objects.import_module_set_name has cognitive complexity 16 (threshold 15). Drivers by points: if/else 3 (10 pts), loops 2 (5 pts), boolean chains 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 · Runner.__init__ (cognitive 16) · ×1

Runner.__init__ (cognitive 16) REDACTED:363 — Runner.__init__ has cognitive complexity 16 (threshold 15). Drivers by points: boolean chains 5, if/else 5, ternaries 4, error handling 1 (2 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 · ChrononRepoValidator._validate_join (cognitive 16) · ×1

ChrononRepoValidator._validate_join (cognitive 16) api/py/ai/chronon/repo/validator.py:387 — ChrononRepoValidator._validate_join has cognitive complexity 16 (threshold 15). Drivers by points: if/else 9 (11 pts), boolean chains 3, loops 1 (2 pts) (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 · ChrononRepoValidator._validate_group_by (cognitive 16) · ×1

ChrononRepoValidator._validate_group_by (cognitive 16) api/py/ai/chronon/repo/validator.py:475 — ChrononRepoValidator._validate_group_by has cognitive complexity 16 (threshold 15). Drivers by points: if/else 10 (13 pts), boolean chains 2, loops 1 (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

REDACTED

D3 · God Classes · MethodTooLong · ×1

MethodTooLong: Row.to api/src/main/scala/ai/chronon/api/Row.scala:130 — MethodTooLong — to runs 111 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. The bar is 100 significant lines; this is 11 over it, 1.11× 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 (21–23 lines × 2) · ×1

Duplicated block (21–23 lines × 2) spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:120 — spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:120-142 | spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:371-391 — 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/ai/chronon/spark/streaming/GroupBy.scala:120` 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, `spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:117` calls `filter` and `spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:370` 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 (18 lines × 2) · ×1

Duplicated block (18 lines × 2) spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:180 — spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:180-197 | spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:191-208 — 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, `spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:187` calls `distribution`, `count` and `spark/src/main/scala/ai/chronon/spark/streaming/GroupBy.scala:178` 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 (16 lines × 2) · ×1

Duplicated block (16 lines × 2) spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:586 — spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:586-602 | spark/src/main/scala/ai/chronon/spark/streaming/JoinSourceRunner.scala:660-675 — 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/ai/chronon/spark/streaming/JoinSourceRunner.scala:586` 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 (11–13 lines × 2) · ×1

Duplicated block (11–13 lines × 2) spark/src/main/scala/ai/chronon/spark/Driver.scala:960 — spark/src/main/scala/ai/chronon/spark/Driver.scala:960-970 | spark/src/main/scala/ai/chronon/spark/streaming/KafkaStreamBuilder.scala:35-47 — 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.

D4 · Code Duplication · Duplicated block (6 lines × 2) · ×1

Duplicated block (6 lines × 2) online/src/main/java/ai/chronon/online/TBaseDecoderFactory.java:126 — online/src/main/java/ai/chronon/online/TBaseDecoderFactory.java:126-131 | online/src/main/java/ai/chronon/online/ThriftDecoder.java:115-120 — 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. 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 (17–19 lines × 2) · ×1

Duplicated block (17–19 lines × 2) airflow/decorators.py:7 — airflow/decorators.py:7-23 | REDACTED:119-137 — 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.

D4 · Code Duplication · Duplicated block (16–17 lines × 2) · ×1

Duplicated block (16–17 lines × 2) api/py/ai/chronon/pyspark/executables.py:419 — api/py/ai/chronon/pyspark/executables.py:419-434 | api/py/ai/chronon/pyspark/executables.py:608-624 — 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 `api/py/ai/chronon/pyspark/executables.py:419` 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 (12–13 lines × 3) · ×1

Duplicated block (12–13 lines × 3) api/py/ai/chronon/pyspark/executables.py:359 — api/py/ai/chronon/pyspark/executables.py:359-371 | api/py/ai/chronon/pyspark/executables.py:546-557 | api/py/ai/chronon/pyspark/executables.py:714-726 — 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 `api/py/ai/chronon/pyspark/executables.py:359` 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.

D4 · Code Duplication · Duplicated block (10–11 lines × 2) · ×1

Duplicated block (10–11 lines × 2) airflow/helpers.py:272 — airflow/helpers.py:272-281 | airflow/helpers.py:302-312 — 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. 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 (13 lines × 2) · ×1

Duplicated block (13 lines × 2) api/py/ai/chronon/group_by.py:197 — api/py/ai/chronon/group_by.py:197-209 | api/py/ai/chronon/join.py:304-330 — 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.

P5 · DR & Backup · No DR/backup evidence · ×1

No DR/backup evidence — A persistence guard (data volume / purge-protection) was found, but no backup, geo-recovery or RTO/RPO controls were evidenced — a volume that survives a container recreate is not a tested restore from catastrophic loss.

Minor — 18 finding(s)

D31 · IaC & Container Security · Low IaC · ×2

REDACTED
REDACTED

D34 · Knowledge Freshness · Most significant orphaned file · ×2

Most significant orphaned file aggregator/src/main/scala/ai/chronon/aggregator/base/SimpleAggregators.scala — One of the orphaned files carrying the most lost knowledge — ranked by size weighted by the file's role in the codebase, the same weighting behind the score above, so core code outranks equally large plumbing. A reasonable place to start a read-through before the aggregate risk above bites.
Most significant orphaned file api/py/ai/chronon/pyspark/executables.py — One of the orphaned files carrying the most lost knowledge — ranked by size weighted by the file's role in the codebase, the same weighting behind the score above, so core code outranks equally large plumbing. A reasonable place to start a read-through before the aggregate risk above bites.

D16 · Bus Factor · Off-boarding risk · ×1

Off-boarding risk: anonymized user #1 — If anonymized user #1 becomes unavailable, 2 significant file(s) lose their only recent owner: aggregator/src/main/scala/ai/chronon/aggregator/row/RowAggregator.scala, spark/src/main/scala/ai/chronon/spark/Comparison.scala. Pair on, review, or document these before any departure.

D16 · Bus Factor · Further sole-owners (lower concentration) · ×1

Further sole-owners (lower concentration) — 3 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 (5 single-owned of 129 analysed files in total, counted over production source files of roughly 2,400 bytes or more, excluding vendored, generated and example/demo trees and test files identified by path convention, largest first; 129 of the 212 production source files in this repository met that bar). They are anonymized user #2 (1 file(s)), anonymized user #3 (1 file(s)), anonymized user #4 (1 file(s)) — spread or document their files in the same way, at lower priority than the named off-boarding risks above.

D20 · ADR Quality · No ADRs found · ×1

No ADRs found — No ADRs found. The recognised ADR directories in this tree were read — `proposals` — and none of their files is a decision record (a README, index or template page does not count). What was searched, so you can tell an empty log from a search that missed one: every directory under the tree (build output, dependencies and VCS metadata excepted), for a document that is either any non-index page inside a recognised ADR directory, whatever its name and however deeply nested (`docs/adr/use-postgres.md`, `docs/adr/2024/0001-x.md`); or a file anywhere whose name is ADR-shaped (`0001-use-postgres.md`, `adr-012-caching.md`); or, when neither turned anything up, a document carrying the decision-record signature (an "Architecture Decision Record" heading, or Status / Context / Decision / Consequences as section headings). A decision log that clears none of these — unnumbered files outside any recognised directory, without those headings — is not seen by this check and this row is then wrong. If that is your case, say so rather than renaming anything; otherwise, consider recording architectural decisions in `docs/adr/`.

D26 · Project Cohesion · Projects may be oversized for their cohesion · ×1

Projects may be oversized for their cohesion — 1 of 2 project(s) overshoot their size bounds, lowering Project Cohesion to 0.0/10. The most over is `(repository root)` (24203 LoC, 473 public types across 20 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.

D29 · Static Analysis (SAST) · REDACTED · ×1

REDACTED

D29 · Static Analysis (SAST) · REDACTED · ×1

REDACTED

D34 · Knowledge Freshness · Concentrated knowledge decay · ×1

Concentrated knowledge decay — 69 of 129 significant files have no living knowledge, while the repository is still being changed at a low rate (26 commit(s) in the last 90 days) — so this is one repo-wide knowledge-decay state, not 69 separate risks. Counted over 129 of the 212 production source files in this repository: the rest are under the ~2,400-byte size floor this dimension measures over. The code moved on without the people who understood these files: document them or schedule a read-through before the next change lands in them.

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 · No ADRs · ×1

No ADRs — No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.

P3 · Security & performance tooling · No SAST · ×1

No SAST — No static application security testing detected. For this repository's stack, add scalafix or scapegoat (or `semgrep --config=auto`, which runs on any language) as a CI step. What was searched, so you can tell an absence from a miss: the 16221 CI workflow file(s) in this repository, and the scanner and linter configuration checked in beside them. A scan that runs outside CI, one configured in your forge's web UI rather than in a committed file, or a tool whose name is none of those this check carries, is not seen — if that is your case the row is wrong, and saying so is more useful than adding a second scanner.

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.

P6 · Release Hygiene · No changelog · ×1

No changelog — No CHANGELOG/HISTORY/RELEASES file — what shipped when isn't easy to reconstruct for support or audit. (Versioning/tagging makes releases traceable, but a changelog records the what.)

Minor — 14 finding(s)

D12 · Dependency Hygiene · Outdated · ×14

Outdated: ch.qos.logback:logback-classic — `ch.qos.logback %% logback-classic` is declared at 1.2.11 in build.sbt, but 1.6.4 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 1.2.11 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: com.datadoghq:java-dogstatsd-client — `com.datadoghq %% java-dogstatsd-client` is declared at 2.7 in build.sbt, but 4.4.5 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 2.7 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: com.github.ben-manes.caffeine:caffeine — `com.github.ben-manes.caffeine %% caffeine` is declared at 2.8.5 in build.sbt, but 3.3.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 2.8.5 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: com.google.code.gson:gson — `com.google.code.gson %% gson` is declared at 2.8.6 in build.sbt, but 2.14.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 2.8.6 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: com.typesafe:config — `com.typesafe %% config` is declared at 1.4.3 in build.sbt, but 1.4.9 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 1.4.3 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.micrometer:micrometer-registry-statsd — `io.micrometer %% micrometer-registry-statsd` is declared at 1.13.6 in build.sbt, but 1.17.1 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 1.13.6 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.netty:netty-all — `io.netty %% netty-all` is declared at 4.1.111.Final in build.sbt, but 4.2.18.Final is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 4.1.111.Final until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.vertx:vertx-config — `io.vertx %% vertx-config` is declared at 4.5.10 in build.sbt, but 5.2.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 4.5.10 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.vertx:vertx-core — `io.vertx %% vertx-core` is declared at 4.5.10 in build.sbt, but 5.2.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 4.5.10 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.vertx:vertx-micrometer-metrics — `io.vertx %% vertx-micrometer-metrics` is declared at 4.5.10 in build.sbt, but 5.2.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 4.5.10 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: io.vertx:vertx-web — `io.vertx %% vertx-web` is declared at 4.5.10 in build.sbt, but 5.2.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 4.5.10 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: net.jodah:typetools — `net.jodah %% typetools` is declared at 0.4.1 in build.sbt, but 0.6.3 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 0.4.1 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: org.apache.thrift:libthrift — `org.apache.thrift %% libthrift` is declared at 0.13.0 in build.sbt, but 0.24.0 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 0.13.0 until the declaration is edited — there is no lockfile refresh that would move it.
Outdated: org.slf4j:slf4j-api — `org.slf4j %% slf4j-api` is declared at 1.7.36 in build.sbt, but 2.0.20 is the current release on Maven Central. An sbt declaration names an exact version, so this repository builds against 1.7.36 until the declaration is edited — there is no lockfile refresh that would move it.

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-e92ba232ed424e1aa278411ee79b8294/history.json --exit-code 0 --source .	0	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-e92ba232ed424e1aa278411ee79b8294/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 .	24	artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilities	osv-scanner	—	osv-scanner --format json --recursive .	9	artifacts/raw/osv-scanner.json
D31 · IaC & Container Security	trivy	—	trivy config --format json --quiet .	30	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.	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	osv-scanner	—	osv-scanner --format json --recursive .	0	artifacts/raw/osv-scanner.json

Run 01a0e932-1aec-76da-9371-4c2590cba282 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Airbnb/chronon

Findings by grade

This survey was produced by

Executive summary

Top priorities

Diagnosis — what's actually going on

Architecture — module dependency matrix

At a glance — Code Health · 85% · Strong ·

At a glance — Architecture · 76% · Adequate · gated by D26 ·

At a glance — Maturity · 70% · Strong ·

At a glance — Readiness · 39% · Weak · gated by P3, P5 ·

At a glance — Security · 62% · Adequate · gated by D29, D31, D36 ·

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

The LLM boundary

Dimensions

Frontend & cross-cutting dimensions

Reference — by lens

Appendix A — Findings (grouped)

Appendix B — Reproduction & audit trail

Downloadable artifacts