Public report — LibOptimization, published 8 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
158findings with an exact file:lineof 176 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
42/92dimensions across the health lenses440 LoC · 13 projects — wide & deep
Executive summary
Read through the Production lens — the standard calibration. *Green* means good enough to run in production. The score is absolute and comparable across repos.
tomitomi3/LibOptimization carries serious gaps (46%). Several issues below can materially affect correctness, security, or the cost of changing it — and propagate to everything that depends on it.
It is strongest in Architecture (92%) — the structure is clean and changes stay contained. Security (89%) is solid too.
The area that most needs attention is Readiness (33%) — releases are harder to depend on — versioning, release notes and dependency hygiene are thin, so consumers can't easily tell what changed or trust an upgrade. Maturity (39%) is the next concern — onboarding is slow — key decisions and the architecture aren't written down, so contributors have to reverse-engineer the intent.
Leadership focus, highest impact first: CI workflow that builds and runs the test suite on every push/PR (CI/CD gates); 1 No tests found finding(s) in Test Distribution (Test Distribution); Start an ADR log (docs/adr/) recording significant decisions… (Architecture documentation).
For scale: Hobby (~440 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
It builds on a genuinely strong Architecture foundation (92%); the priorities above are the highest-leverage way to bring the rest up to that level.
How the score is built — each lens's share of the headlineWidth 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.
IC1 · Skeleton type — most members are unfinished SampleCSharp/Program.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/Program.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/Program.cs
IC1 · Skeleton type — most members are unfinished SampleCSharp/RosenBrock.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/RosenBrock.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/RosenBrock.cs
IC1 · Skeleton type — most members are unfinished SampleCSharp/SimulatedAnnealingSample.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/SimulatedAnnealingSample.cs
IC1 · Hollow method — returns a constant without doing the work SampleCSharp/SimulatedAnnealingSample.cs
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.
How we model this: boilerplate at a scaffolding rate + logic × domain Standard (×1.0) — library/CLI, high decision density × a 0.7× quality factor, at €60–95/h; indicative, ±~30%. 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.
1
Resolve the 1 No tests found finding(s) in Test Distribution.
Of everything flagged, the best return on effort is: Add a CI workflow that builds and runs the test suite on every push/PR. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
→ Add a CI workflow that builds and runs the test suite on every push/PR.
At a glance — Code Health · 64% · Adequate · gated by D2, D18, IC1
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
A06:2021 — Vulnerable & Outdated Components
8
High / Critical
Roadmap
First, establish a CI/CD pipeline to automatically build and test every change. Next, address the missing test coverage to ensure code quality. Then, begin documenting key architectural decisions and organize the project structure to separate production code from tooling. Finally, update the README with a quick-start guide to help new contributors get started.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No tests found finding(s) in Test Distribution.
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. 39 of 42 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 3 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.6 — 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 — 42 dimensions across the health lenses
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, 158 of 176 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
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.
D31 IaC & Container Security — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D32 Data Compliance (PII/GDPR) — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D33 JS/npm Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D36 Supply-chain Provenance & Signing — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D37 Vulnerability-disclosure Policy — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
D38 OSV Dependency Vulnerabilities — scanner not present in this environment — The backing tool was not installed where this scan ran, so this dimension was not scored. Install the tool (or run in the hosted environment, where it is always present) for a graded result.
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 (jscpd) — it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (EF migration scaffolds, *.Designer.cs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only; the generated footprint is reported separately under Solution Shape.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
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.
D11 Test Reliability: Flakiness is inferred from history/markers — Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
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").
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 (EF migrations, designer files, snapshots) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
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.
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.
D24 Comment Value: Comment value (WHY vs WHAT) is an LLM judgement over a bounded sample — it is advisory and cannot weigh a comment against the precise code change it was written to explain.
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 the advisory database — a vulnerability with no published advisory, or in code not declared as a dependency, is not seen.
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.
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.
The LLM boundary
LLM-set scores this run (5): D19, D20, D21, D24, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These 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.
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.
+ 9 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 clsOptDE.DoIteration (cyclomatic 38) finding(s) in Cyclomatic Complexity — start with clsOptDE.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 UnitTestLinearAlgebra.Vec_Product_VectorMatrix (cyclomatic 24) finding(s) in Cyclomatic Complexity — start with UnitTestLinearAlgebra.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 clsOptDEJADE.DoIteration (cyclomatic 23) finding(s) in Cyclomatic Complexity — start with clsOptDEJADE.vb. — 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.
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.
+ 37 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 clsOptDE.DoIteration (cognitive 99) finding(s) in Cognitive Complexity — start with clsOptDE.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 clsOptDEJADE.DoIteration (cognitive 60) finding(s) in Cognitive Complexity — start with clsOptDEJADE.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 DenseMatrix.tred2 (cognitive 59) finding(s) in Cognitive Complexity — start with DenseMatrix.vb. — 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.
Do you agree with this assessment?
D3 · God Classes8.8 / 10Strong✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
Resolve the 4 TooManyMethods finding(s) in God Classes — start with DenseMatrix.vb, DenseVector.vb, UnitTestLinearAlgebra.vb. — One of this dimension's main actionable groups (4 warning-level).
Resolve the 3 FileTooLong finding(s) in God Classes — start with DenseMatrix.vb, UnitTestLinearAlgebra.vb, clsUtil.vb. — One of this dimension's main actionable groups (3 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.
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.
+ 16 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 4 Duplicated block (17 lines × 2) finding(s) in Code Duplication — start with UnitTestLibOptimization.vb (2), UnitTestLinearAlgebra.vb (2). — One of this dimension's main actionable groups (4 warning-level).
Resolve the 3 Duplicated block (12 lines × 2) finding(s) in Code Duplication — start with UnitTestLinearAlgebra.vb (2), clsOptNewtonMethod.vb. — One of this dimension's main actionable groups (3 warning-level).
Resolve the 3 Duplicated block (11 lines × 2) finding(s) in Code Duplication — start with clsOptNelderMead.vb, clsOptNewtonMethod.vb, clsOptRealGAREX.vb. — One of this dimension's main actionable groups (3 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?
D5 · Coupling9.4 / 10Exemplary✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
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.
Detailed fixes: d6_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 · Test Distribution0.0 / 10Critical✓ 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.
Resolve the 1 No tests found finding(s) in Test Distribution. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d9_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D11 · Test Reliability10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether the tests pass reliably, with no flakiness.
Method: Suite re-run N times within tiered wall-clock budgets (unit to e2e); tests failing non-deterministically across runs flagged; guarded tests retried when #if guards detected.
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.
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.
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.
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.
2 source file(s) have their living knowledge concentrated in one author (≥90% of recent, decayed contribution). The largest is SampleCSharp/Program.cs.
Small-team knowledge concentration
What to do
Resolve the 1 Small-team knowledge concentration finding(s) in Bus Factor. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d16_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D17 · Explicit Debt8.4 / 10Strong✓ 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.
Resolve the 13 EmptyCatchBlock finding(s) in Explicit Debt — start with UnitTestLinearAlgebra.vb (13). — One of this dimension's main actionable groups (13 issue-level).
Resolve the 1 ObsoleteWithCallers finding(s) in Explicit Debt — start with DenseMatrix.vb. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 CommentedOutCode finding(s) in Explicit Debt — start with SimulatedAnnealingSample.cs. — One of this dimension's main actionable groups (1 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?
D18 · Solution Shape2.6 / 10Weak✓ Tool-verified
What it measures: Whether the solution is laid out in a sensible, conventional structure.
Method: Solution structure: project count, decomposition, shell-project detection, build success (confirmed failures cap the score); traced to actual .sln files and binaries. Deterministic.
Resolve the 12 Shell project finding(s) in Solution Shape — start with LibOptimization.vbproj (7), SampleVB.vbproj, TestCode.vbproj. — One of this dimension's main actionable groups (12 recommendation-level).
Detailed fixes: d18_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
The single README is a strong documentation set for the LibOptimization numerical optimization library: it includes an excellent English description of what the library does and which algorithms are implemented (including a detailed list of algorithms with their Wikipedia references), links to a tutorial, contact information, a citation format, a recent-change note, and an Introduction section. The document is clipped mid-sentence in the middle of the Algorithms section, so the full outline is visible but not the body; this does not make any sections missing or incomplete. It reads like a well-structured product description for a library rather than a technical reference.
Improve Documentation Quality — currently 8.0/10. — The single README is a strong documentation set for the LibOptimization numerical optimization library: it includes an excellent English description of what the library does and which algorithms are implemented (including a detailed list of algorithms with their Wikipedia references), links to a tutorial, contact information, a citation format, a recent-change note, and an Introduction section. The document is clipped mid-sentence in the middle of the Algorithms section, so the full outline is visible but not the body; this does not make any sections missing or incomplete. It reads like a well-structured product description for a library rather than a technical reference.
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
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.
1 naming inconsistencies across 28 sampled symbols.
Typo in type name: 'Objectice' vs 'Objective'. The first appears to be a misspelling of the second.
What to do
Resolve the 1 Typo in type name finding(s) in Naming Consistency. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d21_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D24 · Comment Value / 10Strong◐ Sampled · advisory
What it measures: Whether comments are worth it — explaining WHY (valuable) rather than WHAT (redundant).
Method: Judged by language model at low temperature (0.0-0.1) on deterministically sampled inline comments with surrounding code; findings verified back to sampled comments by substring match. Advisory, sampled.
16 valuable / 2 redundant across 77 sampled comments; 2 shown with locations.
redundant comment · ×2SampleCSharp/Program.cs:156
What to do
Resolve the 2 redundant comment finding(s) in Comment Value — start with Program.cs (2). — One of this dimension's main actionable groups (2 recommendation-level).
Detailed fixes: d24_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
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).
What it measures: Whether any dependencies have known published vulnerabilities (CVEs), direct or transitive.
Method: NuGet CVE scan via dotnet list package --vulnerable including transitive; severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer. Exhaustive, deterministic; degrades when absent.
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.
2 of 2 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is SampleCSharp/Program.cs.
Further orphaned files (smaller)
What to do
Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d34_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D35 · Change Coupling2.8 / 10Weak✓ 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; coupling through a build step, config, or non-source file isn't seen.
Resolve the 10 Change coupling finding(s) in Change Coupling — start with clsOptPSO.vb (3), clsOptPSOAIW.vb (2), clsOptRealGABLX.vb (2). — One of this dimension's main actionable groups (10 warning-level).
Detailed fixes: d35_recommendation.md · top locations in Appendix A, every location in findings.md.
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.
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 — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).
Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.
Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.
Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.
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.
Other · Code Health — Unreviewed-generation residue: shipped members still throwing NotImplementedException, and placeholder string literals left in non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.
Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.
A shipped member still throws NotImplementedException — generated scaffolding that was never completed. Implement it or remove the dead surface. — RosenBrock.cs:23
What to do
Finish or delete NotImplementedException stubs and replace placeholder literals before shipping.
Other · Code Health — Unfinished work detected by code SHAPE, not keywords: members that only throw a "not implemented" exception, methods that take inputs and return a constant, async methods that never await, dead `if (false)` / `#if false` branches, and skeleton types most of whose members are holes. A real, objective slice of technical debt.
`MyObjectiveFunction` has 2 unfinished members out of 4 — a scaffolded type that was never implemented. — Program.cs:14
`Gradient` looks like it should compute a result but its body just returns a constant — a placeholder return that was never filled in. (×3) — Program.cs:61, RosenBrock.cs:40, SimulatedAnnealingSample.cs:39
`Hessian` looks like it should compute a result but its body just returns a constant — a placeholder return that was never filled in. (×3) — Program.cs:66, RosenBrock.cs:45, SimulatedAnnealingSample.cs:44
`RosenBrock` has 2 unfinished members out of 4 — a scaffolded type that was never implemented. — RosenBrock.cs:11
`MyObjecticeFunctionForSA` has 2 unfinished members out of 4 — a scaffolded type that was never implemented. — SimulatedAnnealingSample.cs:14
A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers). (×4) — Program.cs:251, SimulatedAnnealingSample.cs:125, SimulatedAnnealingSample.cs:126, …
What to do
Finish or delete the unfinished stubs (NotImplementedException / empty / constant-returning bodies) — they are dead surface that looks live.
Clear the softer debt: remove commented-out code and dead branches, re-enable or delete skipped tests, and replace blanket warning suppressions with targeted ones.
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 7 of 7 project(s) that lack one — worth up to 2 pts.
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.
Projects aren't grouped under a src/ folder — production and tooling code are mixed at the root.
Test projects aren't grouped under a tests/ folder — the test surface isn't separable from production code at a glance.
Only 7/13 projects share a common root namespace — the code's module identity is inconsistent.
What to do
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.
Group test projects under tests/ (or test/, spec/) so the test surface is discoverable and CI can scope it.
Adopt a consistent root-namespace convention (a shared prefix, e.g. Acme.*); short project-file/directory names are fine as long as the RootNamespace is uniform.
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 gates0.0 / 10Critical✓ Tool-verified
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.
No CI workflow found (.github/workflows, azure-pipelines.yml, .gitlab-ci.yml, …) — changes aren't gated by an automated build/test.
What to do
Add a CI workflow that builds and runs the test suite on every push/PR.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem/Roslyn scan: CodeQL, Dependabot, secret-scanning, and BenchmarkDotNet presence in pipelines and projects. Exhaustive, deterministic.
Readiness · Performance — Whether the library protects its performance with benchmarks — a BenchmarkDotNet suite, an allocation MemoryDiagnoser, and (ideally) a CI gate. Presence is credited as a bonus, never a deduction.
Method: Repo + source scan: BenchmarkDotNet referenced (csproj/source), [Benchmark]/[MemoryDiagnoser] attribute counts, and a benchmark step in CI — scored as a bonus ladder (absence is neutral, never a deduction). Deterministic, presence detection.
No BenchmarkDotNet suite was found. For a performance-sensitive library, a benchmark guards against silent regressions — but it's a bonus here, not a deduction.
What to do
Add a BenchmarkDotNet project for the hot paths (with [MemoryDiagnoser] to track allocations), and run it in CI to catch regressions.
Readiness · Performance — Whether the code is written to minimise allocations so it doesn't pressure its host's GC — Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc, ValueTask, value-type structs and buffer writers. Reward-only: credited where present, never penalised where a simpler style is fine.
No Span/Memory, pooling (ArrayPool/ObjectPool), stackalloc, ValueTask or buffer-writer usage was found. If this library sits on a hot path, these reduce the GC pressure it puts on its host — a bonus, not a requirement.
What to do
On hot paths, prefer Span<T>/ReadOnlySpan<T>, ArrayPool<T>, stackalloc and ValueTask to cut allocations a consumer would otherwise inherit.
Readiness · Performance — Whether asynchronous code keeps its host responsive — a library awaits with ConfigureAwait(false) (so it never captures and stalls the host's context) and avoids sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) that wastes threads and risks deadlock.
Method: Production-source scan: sync-over-async blocking (.Wait()/.GetAwaiter().GetResult()) counted everywhere, and — for a library with ≥5 awaits — the share of awaits using ConfigureAwait(false). Deterministic, syntax/text detection.
Other · Code Health — Whether the code avoids sync-over-async (deadlock-prone blocking on tasks) and async void.
Method: Roslyn syntax scan: async methods scanned for .Wait()/.GetAwaiter().GetResult() and async-void outside event handlers. Deterministic, hard fact per invocation.
Other · Code Health — Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.
Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.
Other · Code Health — Whether log calls use message templates (queryable) rather than interpolated strings.
Method: Roslyn syntax scan: every log call-site counted; interpolated-string first-argument violations flagged. Population is all log calls, not estimated. Deterministic.
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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.
Not included — 51 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 — no DI registrations detected
AX2 Stateful singletons — no singleton implementations detected
AX6 Interface segregation — no public interfaces
AX7 Slice cohesion — not applicable — not a vertical-slice architecture
AX8 Test isolation — no test/production split to check
AX9 CQS / query purity — no CQRS query handlers detected — query purity is not applicable to this codebase
C1 Data Protection — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C2 Access Controls — No access-control surface detected in the analyzed source — no web/app surface to authorize (no HTTP API or web-UI project) and no authorization code at all (no [Authorize]/policies, no imperative guard methods). Access control is therefore N/A here — this is a library/CLI, which is authorized by its CALLER, not by itself. If this codebase grows request handlers, the dimension reactivates and a default-deny posture is expected then.
C3 Audit Trail — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C4 Data Retention — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
C5 Data-Subject Rights — No personal data detected in the analyzed source — no PII-typed entity/column names (Email, FirstName, DateOfBirth, …), no ASP.NET Identity / user-account model, and no stored user credentials. GDPR data-protection controls are therefore N/A here. If this is intentional, record the no-PII posture in an ADR; if the app does process personal data, name those fields conventionally so this dimension activates.
D10 Test Quality — ~87 lines of test code exist on disk but weren't loaded from the analyzed solution (excluded from the .sln, or co-located/using a test attribute not loaded here), so test quality couldn't be assessed. Include the tests in the analyzed solution to enable this check.
D14 License Compliance — license scan produced no result — the tool ran but its JSON output could not be parsed; the offline NuGet fallback resolved nothing
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — Bounded contexts not declared
D25 ADR Conformance — no ADRs to check
D27 Navigability — symbol resolution incomplete — navigability not assessed
D31 IaC & Container Security — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Data Compliance (PII/GDPR) — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
D36 Supply-chain Provenance & Signing — No CI/build pipeline found (.github/workflows, .gitlab-ci.yml, azure-pipelines.yml, Jenkinsfile, .circleci); there is no build to attest provenance for.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
D8 Code Coverage — Coverage not measured
DM1 Domain Modelling — not run — 0/3 markers found
ED1 Event-Driven — not run — 0/3 markers found
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not run — 0/3 markers found
P12 CI test-gate honesty — no CI workflow found
P2 Observability — This repo is a library, not a deployed service — it has no process to operate, so production observability (structured logging, tracing/metrics, health checks) is N/A. A library may log via an injected ILogger, but the absence of operational telemetry is not a defect here. If it grows a host (web API, worker), the dimension reactivates.
P4 Deployment & Rollback — not evidenced — no deploy/rollback/approval signal in the repo; absence of evidence is not evidence of a manual release
P5 DR & Backup — not evidenced — repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P6 Release Hygiene — not evidenced — no changelog, version stamp or semver release tag in the repo
P7 Outbound HTTP resilience — not applicable — this isn't a service/API/worker
P8 Schema migrations — no EF Core usage detected
P9 Domain vs controller coverage — no coverage report found on disk — run tests with `--collect:"XPlat Code Coverage"` (or in CI) to enable this cross-layer check
S1 Web-Security Posture — No web surface detected in the analyzed source — no HTTP API or web-UI project (no controllers/minimal-API endpoints, no Razor/Blazor views) and no web middleware (HTTPS redirection, HSTS, security headers, cookies). Transport security, security headers, secure cookies, CSRF/input-validation and middleware-order controls are therefore N/A here — this is a library/CLI/worker, not a web app. Crypto hygiene was still checked and found nothing to flag. If this codebase becomes web-facing, the dimension reactivates automatically.
SC1 Supply-chain hygiene — no data
X2 Cancellation propagation — no async methods found
X5 Nullable reference types — no NRT-eligible projects
X6 Hand-rolled structured-format parsing — no data
X7 Silent fallback defaults — no data
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.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseVector (LCOM4 14) LibOptimization/MathTool/DenseVector.vb:8— DenseVector's methods form 14 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: DenseMatrix (LCOM4 6) LibOptimization/MathTool/DenseMatrix.vb:9— DenseMatrix's methods form 6 groups that share no state and don't call each other — a sign it may have several responsibilities. Review whether it splits into focused classes.
Change coupling: clsOptPSOAIW.vb ↔ clsOptPSOChaoticIW.vb LibOptimization/Optimization/clsOptPSOAIW.vb— `LibOptimization/Optimization/clsOptPSOAIW.vb` and `LibOptimization/Optimization/clsOptPSOChaoticIW.vb` change together 78% of the time (18 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptRealGAREX.vb ↔ clsOptRealGASPX.vb LibOptimization/Optimization/clsOptRealGAREX.vb— `LibOptimization/Optimization/clsOptRealGAREX.vb` and `LibOptimization/Optimization/clsOptRealGASPX.vb` change together 78% of the time (25 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptPSOAIW.vb ↔ clsOptPSOLDIW.vb LibOptimization/Optimization/clsOptPSOAIW.vb— `LibOptimization/Optimization/clsOptPSOAIW.vb` and `LibOptimization/Optimization/clsOptPSOLDIW.vb` change together 76% of the time (16 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptPSOChaoticIW.vb ↔ clsOptPSOLDIW.vb LibOptimization/Optimization/clsOptPSOChaoticIW.vb— `LibOptimization/Optimization/clsOptPSOChaoticIW.vb` and `LibOptimization/Optimization/clsOptPSOLDIW.vb` change together 76% of the time (16 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptPSO.vb ↔ clsOptPSOAIW.vb LibOptimization/Optimization/clsOptPSO.vb— `LibOptimization/Optimization/clsOptPSO.vb` and `LibOptimization/Optimization/clsOptPSOAIW.vb` change together 74% of the time (17 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptPSO.vb ↔ clsOptPSOChaoticIW.vb LibOptimization/Optimization/clsOptPSO.vb— `LibOptimization/Optimization/clsOptPSO.vb` and `LibOptimization/Optimization/clsOptPSOChaoticIW.vb` change together 74% of the time (17 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptRealGABLX.vb ↔ clsOptRealGASPX.vb LibOptimization/Optimization/clsOptRealGABLX.vb— `LibOptimization/Optimization/clsOptRealGABLX.vb` and `LibOptimization/Optimization/clsOptRealGASPX.vb` change together 74% of the time (14 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptPSO.vb ↔ clsOptPSOLDIW.vb LibOptimization/Optimization/clsOptPSO.vb— `LibOptimization/Optimization/clsOptPSO.vb` and `LibOptimization/Optimization/clsOptPSOLDIW.vb` change together 71% of the time (15 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsBenchDeJongFunction1.vb ↔ clsBenchDeJongFunction2.vb LibOptimization/BenchmarkFunctions/clsBenchDeJongFunction1.vb— `LibOptimization/BenchmarkFunctions/clsBenchDeJongFunction1.vb` and `LibOptimization/BenchmarkFunctions/clsBenchDeJongFunction2.vb` change together 70% of the time (7 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Change coupling: clsOptRealGABLX.vb ↔ clsOptRealGAREX.vb LibOptimization/Optimization/clsOptRealGABLX.vb— `LibOptimization/Optimization/clsOptRealGABLX.vb` and `LibOptimization/Optimization/clsOptRealGAREX.vb` change together 68% of the time (13 shared commits) with no explicit dependency — a hidden/logical coupling. If they belong together, co-locate them; if not, break the coupling.
Off the main sequence: LibOptimization(net35) — LibOptimization(net35): abstractness 0.04, instability 0.00, distance 0.96 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Coverage not measured — The test suite couldn't be built/run in-image and no coverage report is committed, so line coverage was not measured — and it is EXCLUDED from the score rather than scored on a LoC-ratio proxy. Commit the Cobertura/OpenCover/lcov report your CI already produces (anywhere in the repo), or make the suite runnable in-image, and real coverage will be measured.
Shell project: SampleVB SampleVB/SampleVB.vbproj— `SampleVB` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: TestLibOptimization TestLibOptimization/TestLibOptimization.vbproj— `TestLibOptimization` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: TestCode TestCode/TestCode.vbproj— `TestCode` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: TestLibOptimizationDotNet3.5 TestLibOptimizationDotNet3.5/TestLibOptimizationDotNet3.5.vbproj— `TestLibOptimizationDotNet3.5` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(net35) LibOptimization/LibOptimization.vbproj— `LibOptimization(net35)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(net48) LibOptimization/LibOptimization.vbproj— `LibOptimization(net48)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(netcoreapp2.1) LibOptimization/LibOptimization.vbproj— `LibOptimization(netcoreapp2.1)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(netcoreapp3.0) LibOptimization/LibOptimization.vbproj— `LibOptimization(netcoreapp3.0)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(netcoreapp3.1) LibOptimization/LibOptimization.vbproj— `LibOptimization(netcoreapp3.1)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization(net5.0) LibOptimization/LibOptimization.vbproj— `LibOptimization(net5.0)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: LibOptimization( net8.0) LibOptimization/LibOptimization.vbproj— `LibOptimization( net8.0)` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
Shell project: TestLibOptimizationDotNetCore TestLibOptimizationDotNetCore/TestLibOptimizationDotNetCore.vbproj— `TestLibOptimizationDotNetCore` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
redundant comment SampleCSharp/Program.cs:156— "move initial position" — restates 'Init'; remove or replace with WHY (e.g. why this is the starting point)
redundant comment SampleCSharp/Program.cs:96— "Optimization problem using MyObjectiveFunction" — mirrors 'min f(x)'; remove or replace with WHY (e.g. why this objective)
D16 · Bus Factor· Small-team knowledge concentration · ×1
Small-team knowledge concentration — 2 file(s) are concentrated to one author — the ambient state with 2 active author(s), not 2 separate risks. The signal becomes meaningful as ownership spreads; no per-file action implied now.
Typo in type name: 'Objectice' vs 'Objective'. The first appears to be a misspelling of the second. — Rename 'MyObjecticeFunctionForSA' to 'MyObjectiveFunctionForSA' to match the correct spelling and the other type 'MyObjectiveFunction'. (symbols: SampleCSharp.MyObjecticeFunctionForSA, SampleCSharp.MyObjectiveFunction)
D23 · Boundary Type-Coupling· Bounded contexts not declared · ×1
Bounded contexts not declared — At 14k LoC across 13 projects the codebase is large and multi-module, so explicit bounded contexts are needed. Declare architecture.contexts (≥2) in config to assess cross-boundary type coupling.
D34 · Knowledge Freshness· Further orphaned files (smaller) · ×1
Further orphaned files (smaller) — 2 smaller file(s) also have no living knowledge — folded into the freshness score and metrics rather than listed individually (2 orphaned of 2 analysed files in total).
D18 · Solution Shape· Build did not complete in the analyzer · ×1
Build did not complete in the analyzer — `dotnet build` reported 5 error(s) but no C# compiler diagnostic — an SDK / target-framework / restore mismatch in the analyzer environment, not a code defect (common for an older codebase whose target framework the analyzer's SDK can't build). Solution Shape is scored on structure and is NOT capped; the C# semantic analysis loads independently and is unaffected.
D22 · Internal API Consistency· No exposed public API · ×1
No exposed public API — No intentionally-exposed types (IsPackable or .Contracts) to evaluate.
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.
trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
trivy: not applicable — No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
provenance: not applicable — No CI/build pipeline found (.github/workflows, .gitlab-ci.yml, azure-pipelines.yml, Jenkinsfile, .circleci); there is no build to attest provenance for.
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
osv-scanner: not applicable — No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
0
—
Run 019fdebe-be2f-75f9-a3cd-69e2b558fc67 · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 17 · Warnings: 131 · Recommendations: 20 · Info: 8 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 08-08-2026 @ 00:21 UTC.
Downloadable artifacts
Machine-readable and reproducible from this commit + frozen rubric — drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.