Public report — Owl, 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.
Watchdogby Canine Development 08-08-2026 @ 00:20 UTC Public
Code Health Audit

Mateuszzwierzycki/Owl

no automated testsbounded contexts not declared
48% Weak
CriticalWeakAdequateStrongExemplary
upper third — near Adequate
Security 100% Exemplary Architecture 98% Exemplary Code Health 92% Adequate Maturity 46% Weak Readiness 23% Critical

Hobby · 466 LoC · 9 projects · weakest lens: Readiness (23%)

Grounded in facts. Every number here is computed, not narrated — reproducible, tool-backed, and traceable to a line of code. How to trust this ▸

36/39dimensions tool-verifieddeterministic · confidence 1.0 · 3 LLM-assisted, advisory
74findings with an exact file:lineof 85 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
39/92dimensions across the health lenses466 LoC · 9 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.

mateuszzwierzycki/Owl carries serious gaps (48%). 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 Security (100%) — its security and compliance posture is in good shape. Architecture (98%) is solid too.

The area that most needs attention is Readiness (23%) — 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 (46%) 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 automated tests finding(s) in Code Coverage (Code Coverage); 1 No tests found finding(s) in Test Distribution (Test Distribution).

For scale: Hobby (~466 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.

Encouragingly, the gaps are in documentation and release process — not in the code's correctness, structure or security, which are strong. They're low-risk to close, and doing so would lift the grade without re-engineering anything that already works.

Code Health 92% Adequate · gated by D18 Architecture 98% ★ Exemplary Maturity 46% Weak · gated by D34, M2 Readiness 23% ⚠ Critical · gated by D8, D9, P1, P3 Security 100% ★ Exemplary
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 23% · 47% weightMaturity 46% · 26% weightCode Health 92% · 14% weightArchitecture 98% · 8% weightSecurity 100% · 4% weight

Raise Readiness 23 → 70 (the Healthy floor) ⇒ headline 48 → ~65.

Code composition — where the lines go
Business logic 6%Plumbing 11%Generated 83%
New since the last scan (2+)

2 finding(s) are new versus the previous scan (2026-08-03) — surfaced by this scheduled scan itself, no pull request required.

  • D4 · Duplicated block (15 lines × 2) Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb
  • D4 · Duplicated block (5 lines × 5) Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb

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 — €150–€760
Cost to rebuild€150–€760 (0.1 person-years (3–8 h), ~1 engineer)
Domain complexityStandard — harder problems cost more per line
Quality factor0.7× (at 48% quality) — the last 20% of quality is most of the work
Size & shapeHobby · 45% boilerplate · 19% straight-line · 36% branching logic

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 automated tests finding(s) in Code Coverage.
+17.8 pts · Low effort · Code Coverage
2
Resolve the 1 No tests found finding(s) in Test Distribution.
+17.8 pts · Low effort · Test Distribution
3
Add a CI workflow that builds and runs the test suite on every push/PR.
+23.8 pts · Medium effort · CI/CD gates

Diagnosis — what's actually going on

Highest-leverage move · Medium · Leverage
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 · 92% · Adequate · gated by D18

The Good
D1 · .NET / C# Cyclomatic Complexity 8.8 D2 · .NET / C# Cognitive Complexity 7.3 D3 · .NET / C# God Classes 9.4 D4 · .NET / C# Code Duplication 9.6 D17 · .NET / C# Explicit Debt 9.8 GD1 · Repo Unfinished & placeholder code 10.0 IC1 · Repo Incompleteness & stubs 10.0 X1 · Repo Async correctness 10.0 X3 · Repo Exception handling 10.0 X4 · Repo Structured logging 10.0
The Ugly
D18 · .NET / C# Solution Shape 2.9

At a glance — Architecture · 98% · Exemplary

The Good
D5 · .NET / C# Coupling 9.1 D6 · .NET / C# Cohesion (LCOM4) 8.8 D26 · .NET / C# Project Cohesion 10.0 D35 · .NET / C# Change Coupling 10.0 AX10 · Repo Code composition 10.0 AX3 · Repo Project dependency cycles 10.0 AX4 · Repo Dependency direction 10.0 AX5 · Repo Architecture & structure 10.0

At a glance — Maturity · 46% · Weak · gated by D34, M2

The Good
D15 · .NET / C# Churn × Complexity Hotspots 10.0 D16 · .NET / C# Bus Factor 10.0 D21 · .NET / C# Naming Consistency 7.0 M4 · Repo Documentation accuracy 10.0
The Bad
D19 · .NET / C# Documentation Quality 6.0 M1 · Repo Documentation (README) 6.2 M3 · Repo Folder & project structure 6.0
The Ugly
D24 · .NET / C# Comment Value 2.5 D34 · .NET / C# Knowledge Freshness 0.0 M2 · Repo Architecture documentation 0.0

At a glance — Readiness · 23% · Critical · gated by D8, D9, P1, P3

The Good
D12 · .NET / C# Dependency Hygiene 10.0 D13 · .NET / C# Secret Scanning 10.0
The Bad
P6 · Repo Release Hygiene 5.0
The Ugly
D8 · .NET / C# Code Coverage 0.0 P1 · Repo CI/CD gates 0.0 P3 · Repo Security & performance tooling 0.0

At a glance — Security · 100% · Exemplary

The Good
D28 · .NET / C# Secrets (history) 10.0 D29 · .NET / C# Static Analysis (SAST) 10.0 D30 · .NET / C# Dependency Vulnerabilities 10.0

Roadmap

First, establish a continuous integration pipeline to automatically build and test every change. Next, address the single gap in automated testing by ensuring all code is covered and all tests are properly detected. Then, implement a changelog to track release history and begin documenting key architectural decisions to improve long-term maintainability.

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

Do thisHelpsEffortDimension
Resolve the 1 No automated tests finding(s) in Code Coverage.+17.8 ptsLowCode Coverage
Resolve the 1 No tests found finding(s) in Test Distribution.+17.8 ptsLowTest Distribution
Add a CI workflow that builds and runs the test suite on every push/PR.+23.8 ptsMediumCI/CD gates
Keep a changelog (e.g. Keep-a-Changelog) recording what shipped in each release.+17.8 ptsMediumRelease Hygiene
Resolve the 1 Further orphaned files (smaller) finding(s) in Knowledge Freshness.+8.7 ptsLowKnowledge Freshness
Start an ADR log (docs/adr/) recording significant decisions and their rationale.+13.1 ptsMediumArchitecture documentation
Resolve the 1 redundant comment finding(s) in Comment Value — start with ActivationLayer.cs.+6.5 ptsLowComment Value
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.+10.4 ptsMediumFolder & project structure

File quality

Per-file score 0–10 — a quality signature. Of 43 files carrying findings, judged against the Production bar: 0% slop · 30% mixed · 70% near-clean.

FileScoreBandWorst signal
Owl.Core/IO/TensorSerialization.vb6.0MixedExplicit Debt: TodoComment
Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb6.3MixedCyclomatic Complexity: ConstructFromFeatures.SolveInstance (cyclomatic 38)
Owl.Core/TensorSets/TensorSet.vb6.7MixedExplicit Debt: TodoComment
Owl.Core/Tensors/Tensor.vb7.0MixedGod Classes: TooManyMethods: Tensor
Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb7.2MixedCognitive Complexity: NetworkPreview_Attributes.CreateImage (cognitive 31)
Owl.Learning/Clustering/KMeansEngine.vb7.2MixedCognitive Complexity: KMeansEngine.RunOnce (cognitive 18)
Owl.GH.Common/Components/OwlMultithreadedBase.vb7.6MixedExplicit Debt: EmptyCatchBlock
Owl.GH.Common/Components/ImageComponent_Attributes.vb7.8MixedCyclomatic Complexity: ImageComponent_Attributes.Render (cyclomatic 17)
Owl.Accord.Extensions/Visualization/Visualization.vb7.8MixedCognitive Complexity: NetworkDrawing.NetworkImage (cognitive 31)
Owl.Accord.GH/Components/Backpropagation/BackOwl.vb7.8MixedCognitive Complexity: BackOwl.SolveInstance (cognitive 23)
Owl.GH/Components/Owl/Display/TensorSetPolylines.vb7.8MixedCognitive Complexity: TensorSetPolylines.SolveInstance (cognitive 20)
Owl.GH/Params/Param_OwlFiles.vb7.8MixedCode Duplication: Duplicated block (11 lines × 2)
Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb7.8MixedCode Duplication: Duplicated block (9 lines × 2)
Owl.GH/Components/Owl/Display/TensorSetPointCloud.vb8.2Near-cleanExplicit Debt: TodoComment
Owl.Learning/Networks/Functions/NeuronFunctions.vb8.2Near-cleanExplicit Debt: TodoComment
Owl.GH/Components/Owl/Display/Tensor2DPreview.vb8.5Near-cleanCognitive Complexity: Tensor2dPreview.SolveInstance (cognitive 31)
Owl.Accord.Extensions/Extensions/AccordExtensions.vb8.5Near-cleanCognitive Complexity: NetworkExtensions.TrimNetwork (cognitive 24)
Owl.Accord.GH/Components/Unsupervised/TSNE.vb8.5Near-cleanCognitive Complexity: TSNEthread.SolveInstance (cognitive 24)
Owl.Core/Visualization/Plots.vb8.5Near-cleanCognitive Complexity: PlotFactory.TensorSetPlot (cognitive 17)
Owl.Learning/Images/Pooling.vb8.5Near-cleanCognitive Complexity: MaxPooling.Apply (cognitive 17)

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. 36 of 39 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 — 39 dimensions across the health lenses
D1D2D3D4D5D6D8D9D12D13D15D16D17D18D19D21D24D26D28D29D30D34D35AX10AX3AX4AX5GD1IC1M1M2M3M4P1P3P6X1X3X4

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
  1. 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, 74 of 85 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.)
  2. 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.
  3. 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.

MethodBacksVersionEvaluator
Roslyn static analysisComplexity, cohesion, coupling, dead code, API surface, layering5.3.0✓ deterministic
Native secret scannerHardcoded secrets / credentials1.0.0✓ deterministic
jscpdCode duplication—✓ deterministic
Coverage (coverlet / dotnet-coverage)Line & branch coverage10.0.301✓ deterministic
NuGet / dotnetOutdated, vulnerable & deprecated dependencies10.0.301✓ deterministic
git / LibGit2SharpChurn hotspots, knowledge concentration, history2.43.0 · 0.31.0✓ deterministic
gitleaks · semgrep · trivy · checkovSecrets in history, SAST, CVEs, IaC & container, PII / GDPR1.86.0 · 0.69.3✓ deterministic
LLM (sampled · advisory)Documentation quality, ADR conformance, naming — sampled over a bounded sample; advisory, never a deterministic measurementLocal LLM◐ LLM · sampled · advisory

Every finding is locatable in findings.md. Run 019fdebe-943a-728f-a58b-7f76db3db12f.

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.

  • 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.
  • D8 Code Coverage: Coverage is measured by building and running the suite (`dotnet test --collect`) inside Watchdog's isolated image — the target repo is never modified, and nothing on your systems runs. So coverage exists only when the suite builds and runs within the inline time budget; one that needs external services, can't build, or exceeds the budget yields no coverage (D8 then degrades to not-measured, not a low score). Line coverage also says nothing about assertion quality.
  • 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").
  • 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.
  • 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.
  • 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, 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.

Dimensions

D1 · Cyclomatic Complexity8.8 / 10Strong✓ 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 8.8 / 10 · rule-coverage 100% · ceiling Prevented

3 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was ConstructFromFeatures.SolveInstance at 38.

ConstructFromFeatures.SolveInstance (cyclomatic 38)Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb:36
TensorSerialization.SaveTensorsIDX (cyclomatic 19)Owl.Core/IO/TensorSerialization.vb:599
ImageComponent_Attributes.Render (cyclomatic 17)Owl.GH.Common/Components/ImageComponent_Attributes.vb:308

What to do

  1. Resolve the 1 ConstructFromFeatures.SolveInstance (cyclomatic 38) finding(s) in Cyclomatic Complexity — start with ConstructFromFeatures.vb. — One of this dimension's main actionable groups (1 warning-level).
  2. Resolve the 1 TensorSerialization.SaveTensorsIDX (cyclomatic 19) finding(s) in Cyclomatic Complexity — start with TensorSerialization.vb. — One of this dimension's main actionable groups (1 warning-level).
  3. Resolve the 1 ImageComponent_Attributes.Render (cyclomatic 17) finding(s) in Cyclomatic Complexity — start with ImageComponent_Attributes.vb. — One of this dimension's main actionable groups (1 warning-level).
  4. 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.

D2 · Cognitive Complexity7.3 / 10Strong✓ 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 7.3 / 10 · rule-coverage 100% · ceiling Prevented

15 method(s) exceeded the cognitive complexity threshold of 15; the worst was ConstructFromFeatures.SolveInstance at 61.

NetworkDrawing.NetworkImage (cognitive 31) · ×2Owl.Accord.Extensions/Visualization/Visualization.vb:10
ConstructFromFeatures.SolveInstance (cognitive 61)Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb:36
ImageComponent_Attributes.Render (cognitive 40)Owl.GH.Common/Components/ImageComponent_Attributes.vb:308
NetworkPreview_Attributes.CreateImage (cognitive 31)Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:64
Tensor2dPreview.SolveInstance (cognitive 31)Owl.GH/Components/Owl/Display/Tensor2DPreview.vb:45

+ 9 more group(s) — more in Appendix A; the complete list is findings.md.

What to do

  1. Resolve the 2 NetworkDrawing.NetworkImage (cognitive 31) finding(s) in Cognitive Complexity — start with Visualization.vb (2). — One of this dimension's main actionable groups (2 warning-level).
  2. Resolve the 1 ConstructFromFeatures.SolveInstance (cognitive 61) finding(s) in Cognitive Complexity — start with ConstructFromFeatures.vb. — One of this dimension's main actionable groups (1 warning-level).
  3. Resolve the 1 ImageComponent_Attributes.Render (cognitive 40) finding(s) in Cognitive Complexity — start with ImageComponent_Attributes.vb. — One of this dimension's main actionable groups (1 warning-level).
  4. 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.

D3 · God Classes9.4 / 10Exemplary✓ 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 9.4 / 10 · rule-coverage 100% · ceiling Prevented

2 god class(es) detected.

FileTooLong: IO/TensorSerialization.vbOwl.Core/IO/TensorSerialization.vb:0
ClassTooLong: TensorSerializationOwl.Core/IO/TensorSerialization.vb:0
TooManyMethods: TensorOwl.Core/Tensors/Tensor.vb:0

✓ On the Gold path — maintain.

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

D4 · Code Duplication9.6 / 10Exemplary✓ 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 9.6 / 10 · rule-coverage 100% · ceiling Verified

13 duplicated block group(s) detected.

Duplicated block (9 lines × 2) · ×3Owl.Learning/Clustering/KMeansEngine.vb:171
Duplicated block (10 lines × 2) · ×2Owl.Core/Images/Image operations/ImageConverters.vb:107
Duplicated block (15 lines × 2)Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:242
Duplicated block (13 lines × 2)Owl.Learning.Neuro/BackpropagationLearning.cs:194
Duplicated block (12 lines × 2)Owl.Learning/Clustering/KMeansEngine.vb:207

+ 5 more group(s) — more in Appendix A; the complete list is findings.md.

✓ On the Gold path — maintain.

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

D5 · Coupling9.1 / 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.

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

9 projects, 0 dependency cycle(s), 0 unstable depended-on project(s).

Off the main sequence: Owl.Core

✓ On the Gold path — maintain.

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

D6 · Cohesion (LCOM4)8.8 / 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 8.8 / 10 · rule-coverage 100% · ceiling Verified

13 of 132 classes have LCOM4 above 3.

Low cohesion: TensorSet (LCOM4 11) · ×13Owl.Core/TensorSets/TensorSet.vb:11

What to do

  1. Resolve the 13 Low cohesion finding(s) in Cohesion (LCOM4) — start with ClusterDirections.vb, ConstructFromFeatures.vb, GH_ActivationNetwork.vb. — One of this dimension's main actionable groups (13 warning-level).
  2. 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.

D8 · Code Coverage0.0 / 10Critical✓ Tool-verified

What it measures: How much of the code is actually exercised by tests.

Method: Coverage from coverlet runs or committed reports (Cobertura/OpenCover/lcov), computed per-file with structured exclusions for generated, trivial, and glue code. When the suite can't be built/run in-image AND no report is committed, coverage is reported NOT-MEASURED (excluded from the score) with the precondition to make it measurable — never a LoC-ratio proxy folded in as if measured. Deterministic.

Maturity: Documented → Verified → Prevented · effective 0.0 / 10 · rule-coverage 100% · ceiling Verified

No automated tests — the solution has no test code.

No automated tests

What to do

  1. Resolve the 1 No automated tests finding(s) in Code Coverage. — One of this dimension's main actionable groups (1 issue-level).
  2. Enforce Code Coverage in CI to reach Verified (currently Documented). — Hardens enforcement from Documented toward Verified — provenance only; does not change the score.

Detailed fixes: d8_recommendation.md · top locations in Appendix A, every location in findings.md.

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.

Maturity: Documented → Verified → Prevented · effective 0.0 / 10 · rule-coverage 100% · ceiling Documented

No test projects found.

No tests found

What to do

  1. 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.

D12 · Dependency Hygiene10.0 / 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 10.0 / 10 · rule-coverage 100% · ceiling Verified

0 outdated, 0 vulnerable, 0 deprecated packages.

✓ On the Gold path — maintain.

Detailed fixes: d12_recommendation.md.

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.

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.

D16 · Bus Factor10.0 / 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

No source file's living knowledge is concentrated in a single author.

✓ On the Gold path — maintain.

Detailed fixes: d16_recommendation.md.

D17 · Explicit Debt9.8 / 10Exemplary✓ 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 9.8 / 10 · rule-coverage 100% · ceiling Prevented

9 deducted debt markers + 0 dead symbols across 13482 LoC (0.1/KLoC) → score 9.8.

EmptyCatchBlockOwl.GH.Common/Components/OwlMultithreadedBase.vb:100
TodoComment · ×8Owl.Core/IO/TensorSerialization.vb:139

✓ On the Gold path — maintain.

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

D18 · Solution Shape2.9 / 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.

Maturity: Documented → Verified → Prevented · effective 2.9 / 10 · rule-coverage 100% · ceiling Documented

9 projects, 6 .cs files, 13482 hand-written lines of code (13482 production / 0 test), plus 2348 generated (EF migrations / designer / snapshots, excluded from quality), 13 inter-project edges (build failed).

Monorepo: only 1 of 2 solutions was scored
Shell project: Owl.Core · ×8Owl.Core/Owl.Core.vbproj
Build did not complete in the analyzer

What to do

  1. Resolve the 8 Shell project finding(s) in Solution Shape — start with Owl.Accord.Extensions.vbproj, Owl.Accord.GH.Common.vbproj, Owl.Accord.GH.vbproj. — One of this dimension's main actionable groups (8 recommendation-level).
  2. Resolve the 1 Monorepo finding(s) in Solution Shape. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d18_recommendation.md · top locations in Appendix A, every location in findings.md.

D19 · Documentation Quality / 10Adequate◐ 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 Adequate / 10 · rule-coverage 100% · ceiling Documented

Owl's documentation is mostly descriptive but lacks structure: an Intro section gives a vague overview of what each solution does (e.g. 'expression evaluation functions'), while the Solutions list enumerates eight projects with only one entry ('Owl.ParamSetup') giving any setup guidance. The owl.core README shows the most detail, covering types and parameters for GH_Goo but not components or workflows; the gh.common README is clipped mid-sentence and the owl.learning solution remains undocumented. Coverage across all four Owl namespaces (core/learning/gh/common) is 0/38 at 8%, indicating gaps in the documentation set.

Low XML-doc coverage: Owl.Learning.NeuroOwl.Learning.Neuro/Owl.Learning.Neuro.csproj
XML-doc coverage: Owl.Core · ×8Owl.Core/Owl.Core.vbproj

What to do

  1. Resolve the 1 Low XML-doc coverage finding(s) in Documentation Quality — start with Owl.Learning.Neuro.csproj. — One of this dimension's main actionable groups (1 warning-level).

Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.

D21 · Naming Consistency / 10Strong◐ 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 Strong / 10 · rule-coverage 100% · ceiling Verified

2 naming inconsistencies across 50 sampled symbols.

The concept of counting inputs is named 'InputsCount' in some classes but 'InputsCount' in others. However, looking at the list, all three use 'InputsCount'. Wait, let me re-read carefully. Ah, there is a parameter named 'inputs' vs 'input' vs 'input' vs 'output' vs 'desiredOutput'. Let's look for naming inconsistencies of the same concept.
Inconsistency in naming the collection of components: 'Neurons' for a layer, 'Layers' for a network. While distinct, the pattern of pluralizing the component name is consistent. However, there is a parameter naming inconsistency: 'input' vs 'inputs' vs 'desiredOutput' vs 'output'. Specifically, 'input' (singular) is used in BackPropagationLearning.CalculateError and ActivationNeuron.Compute, while 'inputs' (plural) is used in BackPropagationLearning.Run and ActivationLayer.Compute. This is a minor inconsistency in parameter naming for the same concept (the input data).

What to do

  1. Resolve the 1 The concept of counting inputs is named 'InputsCount' in some classes… finding(s) in Naming Consistency. — One of this dimension's main actionable groups (1 recommendation-level).
  2. Resolve the 1 Inconsistency in naming the collection of components 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.

D24 · Comment Value / 10Weak◐ 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.

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

0 valuable / 1 redundant across 64 sampled comments; 1 shown with locations.

redundant commentOwl.Learning.Neuro/ActivationLayer.cs:7

What to do

  1. Resolve the 1 redundant comment finding(s) in Comment Value — start with ActivationLayer.cs. — One of this dimension's main actionable groups (1 recommendation-level).

Detailed fixes: d24_recommendation.md · top locations in Appendix A, every location in findings.md.

D26 · Project Cohesion10.0 / 10Exemplary✓ 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 10.0 / 10 · rule-coverage 100% · ceiling Documented

0 of 9 projects flagged as possibly oversized/incoherent.

✓ On the Gold path — maintain.

Detailed fixes: d26_recommendation.md.

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: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.

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.

D29 · Static Analysis (SAST)10.0 / 10Exemplary○ Nothing flagged

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 10.0 / 10 · rule-coverage 100% · ceiling Documented

semgrep found no security issues.

✓ On the Gold path — maintain.

Detailed fixes: d29_recommendation.md.

D30 · Dependency Vulnerabilities10.0 / 10Exemplary○ Nothing flagged

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.

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

No known-vulnerable NuGet packages (direct or transitive).

✓ On the Gold path — maintain.

Detailed fixes: d30_recommendation.md.

D34 · Knowledge Freshness0.0 / 10Critical✓ 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 0.0 / 10 · rule-coverage 100% · ceiling Documented

1 of 1 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is Owl.Learning.Neuro/BackpropagationLearning.cs.

Further orphaned files (smaller)

What to do

  1. 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.

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; coupling through a build step, config, or non-source file isn't seen.

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.

Frontend & cross-cutting dimensions

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

AX10 · Code composition10.0 / 10Exemplary✓ Tool-verified

Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified.

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).
AX3 · Project dependency cycles10.0 / 10Exemplary✓ Tool-verified

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

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

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

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

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

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.

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

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.

IC1 · Incompleteness & stubs10.0 / 10Exemplary○ Nothing flagged

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.

Method: Roslyn syntax scan: incompleteness by code shape (constant-returning methods, async-never-await, #if false branches, skeleton types), not keyword-gated. Deterministic, code-shape heuristic.

M1 · Documentation (README)6.2 / 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 8 of 9 project(s) that lack one — worth up to 1.8 pts.
M2 · Architecture documentation0.0 / 10Critical✓ 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 — decisions aren't captured for future maintainers.
  • No C4/PlantUML/Mermaid diagram or architecture.md — the high-level shape isn't documented.

What to do

  • Start an ADR log (docs/adr/) recording significant decisions and their rationale.
  • Add a C4 context/container diagram (Structurizr, PlantUML or Mermaid) or an architecture.md overview.
M3 · Folder & project structure6.0 / 10Adequate✓ 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.

  • 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.

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.
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.

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.
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/Roslyn scan: CodeQL, Dependabot, secret-scanning, and BenchmarkDotNet presence in pipelines and projects. Exhaustive, deterministic.

  • No static application security testing (CodeQL / security analyzers / codehealth) detected.

What to do

  • Add a SAST step (e.g. CodeQL) or a security analyzer package.
  • Enable Dependabot/Renovate or a dependency-review gate.
  • Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
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.
X1 · Async correctness10.0 / 10Exemplary○ Nothing flagged

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

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

X3 · Exception handling10.0 / 10Exemplary○ Nothing flagged

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.

X4 · Structured logging10.0 / 10Exemplary○ Nothing flagged

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.

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.

LensScoreRatingImpact
Code Health92%Adequate — gated by D18Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Architecture98%ExemplarySolid.
Maturity46%Weak — gated by D34, M2Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Readiness23%Critical — gated by D8, D9, P1, P3Capped at Fair by a Critical contributor — resolve it before relying on this lens.
Security100%ExemplaryStrongest area.
Not included — 54 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 — No tests in the analyzed solution to assess for quality.
  • D11 Test Reliability — Test reliability not included
  • 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
  • D20 ADR Quality — N/A — ADRs are expected on deployable products with a user-facing host, not consumed libraries; no ADR log is required here.
  • 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
  • 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
  • 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
  • PF1 Benchmark discipline — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
  • PF2 Allocation hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
  • PF3 Async & latency hygiene — Performance is assessed only for perf-relevant repos — a packaged library, one that ships benchmarks, or one already using allocation-aware APIs. This repo isn't one, so the Performance lens is not applicable and is excluded from the score.
  • 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.

Issue — 2 finding(s)
D17 · Explicit Debt · EmptyCatchBlock · ×1
  • EmptyCatchBlock Owl.GH.Common/Components/OwlMultithreadedBase.vb:100 — empty catch block
D8 · Code Coverage · No automated tests · ×1
  • No automated tests — No automated tests — the solution has no test code. Untested code is the largest single risk to changing it safely.
Warning — 58 finding(s)
D6 · Cohesion (LCOM4) · Low cohesion · ×13
  • Low cohesion: TensorSet (LCOM4 11) Owl.Core/TensorSets/TensorSet.vb:11 — TensorSet's methods form 11 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: TensorBase (LCOM4 8) Owl.Core/Tensors/TensorBase.vb:8 — TensorBase's methods form 8 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: ConstructFromFeatures (LCOM4 6) Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb:1 — ConstructFromFeatures'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: Tensor (LCOM4 5) Owl.Core/Tensors/Tensor.vb:6 — Tensor's methods form 5 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: GH_OwlFilePath (LCOM4 5) Owl.GH.Common/Goos/GH_OwlFilePath.vb:4 — GH_OwlFilePath's methods form 5 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: GH_ActivationNetwork (LCOM4 5) Owl.Accord.GH.Common/Goos/GH_ActivationNetwork.vb:7 — GH_ActivationNetwork's methods form 5 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: ClusterDirections (LCOM4 5) Owl.GH/Components/Owl.Learning/Unsupervised/ClusterDirections.vb:3 — ClusterDirections's methods form 5 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: RunProcess (LCOM4 5) Owl.GH/Components/Owl/Scripting/RunProcess.vb:4 — RunProcess's methods form 5 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: GH_OwlNetwork (LCOM4 4) Owl.GH.Common/Goos/GH_OwlNetwork.vb:8 — GH_OwlNetwork's methods form 4 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: GH_OwlTensor (LCOM4 4) Owl.GH.Common/Goos/GH_OwlTensor.vb:7 — GH_OwlTensor's methods form 4 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: GH_OwlTensorSet (LCOM4 4) Owl.GH.Common/Goos/GH_OwlTensorSet.vb:6 — GH_OwlTensorSet's methods form 4 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: GH_OwlQAgent (LCOM4 4) Owl.GH.Common/Goos/GH_OwlQAgent.vb:6 — GH_OwlQAgent's methods form 4 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: GH_Trigger (LCOM4 4) Owl.GH.Common/Goos/GH_Trigger.vb:4 — GH_Trigger's methods form 4 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.
D17 · Explicit Debt · TodoComment · ×8
  • TodoComment Owl.Core/IO/TensorSerialization.vb:139 — 'TODO export bitmaps — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Core/IO/TensorSerialization.vb:251 — 'TODO cleanup — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Core/IO/TensorSerialization.vb:380 — 'TODO fucky, but let it stay here for now. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Core/IO/TensorSerialization.vb:477 — 'TODO fucky, but let it stay here for now. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Core/IO/TensorSerialization.vb:490 — 'TODO fucky, but let it stay here for now. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Core/TensorSets/TensorSet.vb:270 — 'TODO this seems to work — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.GH/Components/Owl/Display/TensorSetPointCloud.vb:7 — 'TODO implement idisposable — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
  • TodoComment Owl.Learning/Networks/Functions/NeuronFunctions.vb:14 — 'TODO function — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: PROJ-123`), so the task is planned where tasks live and the ticket links back to the code.
D4 · Code Duplication · Duplicated block (9 lines × 2) · ×3
  • Duplicated block (9 lines × 2) Owl.Learning/Clustering/KMeansEngine.vb:171 — Owl.Learning/Clustering/KMeansEngine.vb:171-179 | Owl.Learning/Clustering/KMeansEngine.vb:394-402
  • Duplicated block (9 lines × 2) Owl.Learning/Clustering/KMeansEngine.vb:189 — Owl.Learning/Clustering/KMeansEngine.vb:189-197 | Owl.Learning/Clustering/KMeansEngine.vb:412-420
  • Duplicated block (9 lines × 2) Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb:51 — Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb:51-59 | Owl.GH/Components/Owl.Learning/Reinforcement/1/ConstructQLearn.vb:40-48
D2 · Cognitive Complexity · NetworkDrawing.NetworkImage (cognitive 31) · ×2
  • NetworkDrawing.NetworkImage (cognitive 31) Owl.Accord.Extensions/Visualization/Visualization.vb:10 — NetworkDrawing.NetworkImage has cognitive complexity 31 (threshold 15).
  • NetworkDrawing.NetworkImage (cognitive 31) Owl.Accord.Extensions/Visualization/Visualization.vb:149 — NetworkDrawing.NetworkImage has cognitive complexity 31 (threshold 15).
D4 · Code Duplication · Duplicated block (10 lines × 2) · ×2
  • Duplicated block (10 lines × 2) Owl.Core/Images/Image operations/ImageConverters.vb:107 — Owl.Core/Images/Image operations/ImageConverters.vb:107-116 | Owl.Core/Images/Image operations/ImageConverters.vb:154-163
  • Duplicated block (10 lines × 2) Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:45 — Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:45-54 | Owl.GH/Components/Owl/Obsolete/TensorSetPreview_Attributes.vb:40-49
D1 · Cyclomatic Complexity · ConstructFromFeatures.SolveInstance (cyclomatic 38) · ×1
  • ConstructFromFeatures.SolveInstance (cyclomatic 38) Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb:36 — ConstructFromFeatures.SolveInstance has cyclomatic complexity 38 (threshold 15).
D1 · Cyclomatic Complexity · TensorSerialization.SaveTensorsIDX (cyclomatic 19) · ×1
  • TensorSerialization.SaveTensorsIDX (cyclomatic 19) Owl.Core/IO/TensorSerialization.vb:599 — TensorSerialization.SaveTensorsIDX has cyclomatic complexity 19 (threshold 15).
D1 · Cyclomatic Complexity · ImageComponent_Attributes.Render (cyclomatic 17) · ×1
  • ImageComponent_Attributes.Render (cyclomatic 17) Owl.GH.Common/Components/ImageComponent_Attributes.vb:308 — ImageComponent_Attributes.Render has cyclomatic complexity 17 (threshold 15).
D18 · Solution Shape · Monorepo · ×1
  • Monorepo: only 1 of 2 solutions was scored — This repository contains 2 .NET solutions, but a scan analyzes ONE. Every score, lens, and finding here reflects only `Owl.sln` — the other 1 (`Owl.ParamSetup/Owl.ParamSetup.sln`) were not analyzed and are not represented in the headline. To cover them, scan each solution as its own target and group them in a Solution or Product for a portfolio roll-up. If a secondary solution is an archived or vendored tree, declare it — `.gitattributes` (`path/** linguist-vendored`) or `.editorconfig` (`[path/**] generated_code = true`) — to exclude it from discovery the same way generated code is.
D19 · Documentation Quality · Low XML-doc coverage · ×1
  • Low XML-doc coverage: Owl.Learning.Neuro Owl.Learning.Neuro/Owl.Learning.Neuro.csproj — Owl.Learning.Neuro: 8 % XML-doc coverage (3/38).
D2 · Cognitive Complexity · ConstructFromFeatures.SolveInstance (cognitive 61) · ×1
  • ConstructFromFeatures.SolveInstance (cognitive 61) Owl.GH/Components/Owl/Convert/ConstructFromFeatures.vb:36 — ConstructFromFeatures.SolveInstance has cognitive complexity 61 (threshold 15).
D2 · Cognitive Complexity · ImageComponent_Attributes.Render (cognitive 40) · ×1
  • ImageComponent_Attributes.Render (cognitive 40) Owl.GH.Common/Components/ImageComponent_Attributes.vb:308 — ImageComponent_Attributes.Render has cognitive complexity 40 (threshold 15).
D2 · Cognitive Complexity · NetworkPreview_Attributes.CreateImage (cognitive 31) · ×1
  • NetworkPreview_Attributes.CreateImage (cognitive 31) Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:64 — NetworkPreview_Attributes.CreateImage has cognitive complexity 31 (threshold 15).
D2 · Cognitive Complexity · Tensor2dPreview.SolveInstance (cognitive 31) · ×1
  • Tensor2dPreview.SolveInstance (cognitive 31) Owl.GH/Components/Owl/Display/Tensor2DPreview.vb:45 — Tensor2dPreview.SolveInstance has cognitive complexity 31 (threshold 15).
D2 · Cognitive Complexity · NetworkExtensions.TrimNetwork (cognitive 24) · ×1
  • NetworkExtensions.TrimNetwork (cognitive 24) Owl.Accord.Extensions/Extensions/AccordExtensions.vb:45 — NetworkExtensions.TrimNetwork has cognitive complexity 24 (threshold 15).
D2 · Cognitive Complexity · TSNEthread.SolveInstance (cognitive 24) · ×1
  • TSNEthread.SolveInstance (cognitive 24) Owl.Accord.GH/Components/Unsupervised/TSNE.vb:127 — TSNEthread.SolveInstance has cognitive complexity 24 (threshold 15).
D2 · Cognitive Complexity · BackOwl.SolveInstance (cognitive 23) · ×1
  • BackOwl.SolveInstance (cognitive 23) Owl.Accord.GH/Components/Backpropagation/BackOwl.vb:43 — BackOwl.SolveInstance has cognitive complexity 23 (threshold 15).
D2 · Cognitive Complexity · TensorSetPolylines.SolveInstance (cognitive 20) · ×1
  • TensorSetPolylines.SolveInstance (cognitive 20) Owl.GH/Components/Owl/Display/TensorSetPolylines.vb:77 — TensorSetPolylines.SolveInstance has cognitive complexity 20 (threshold 15).
D2 · Cognitive Complexity · KMeansEngine.RunOnce (cognitive 18) · ×1
  • KMeansEngine.RunOnce (cognitive 18) Owl.Learning/Clustering/KMeansEngine.vb:204 — KMeansEngine.RunOnce has cognitive complexity 18 (threshold 15).
D2 · Cognitive Complexity · PlotFactory.TensorSetPlot (cognitive 17) · ×1
  • PlotFactory.TensorSetPlot (cognitive 17) Owl.Core/Visualization/Plots.vb:39 — PlotFactory.TensorSetPlot has cognitive complexity 17 (threshold 15).
D2 · Cognitive Complexity · MaxPooling.Apply (cognitive 17) · ×1
  • MaxPooling.Apply (cognitive 17) Owl.Learning/Images/Pooling.vb:38 — MaxPooling.Apply has cognitive complexity 17 (threshold 15).
D2 · Cognitive Complexity · DisplayCompute.SolveInstance (cognitive 17) · ×1
  • DisplayCompute.SolveInstance (cognitive 17) Owl.Accord.GH/Components/Display/DisplayCompute.vb:53 — DisplayCompute.SolveInstance has cognitive complexity 17 (threshold 15).
D2 · Cognitive Complexity · TensorSetPolylines.DrawViewportWires (cognitive 17) · ×1
  • TensorSetPolylines.DrawViewportWires (cognitive 17) Owl.GH/Components/Owl/Display/TensorSetPolylines.vb:134 — TensorSetPolylines.DrawViewportWires has cognitive complexity 17 (threshold 15).
D3 · God Classes · FileTooLong · ×1
  • FileTooLong: IO/TensorSerialization.vb Owl.Core/IO/TensorSerialization.vb:0 — FileTooLong — 515 lines.
D3 · God Classes · ClassTooLong · ×1
  • ClassTooLong: TensorSerialization Owl.Core/IO/TensorSerialization.vb:0 — ClassTooLong — 509 lines, 17 methods.
D3 · God Classes · TooManyMethods · ×1
  • TooManyMethods: Tensor Owl.Core/Tensors/Tensor.vb:0 — TooManyMethods — 367 lines, 40 methods.
D4 · Code Duplication · Duplicated block (15 lines × 2) · ×1
  • Duplicated block (15 lines × 2) Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:242 — Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:242-256 | Owl.GH/Components/Owl/Obsolete/TensorSetPreview_Attributes.vb:185-198
D4 · Code Duplication · Duplicated block (13 lines × 2) · ×1
  • Duplicated block (13 lines × 2) Owl.Learning.Neuro/BackpropagationLearning.cs:194 — Owl.Learning.Neuro/BackpropagationLearning.cs:194-206 | Owl.Learning.Neuro/BackpropagationLearning.cs:220-232
D4 · Code Duplication · Duplicated block (12 lines × 2) · ×1
  • Duplicated block (12 lines × 2) Owl.Learning/Clustering/KMeansEngine.vb:207 — Owl.Learning/Clustering/KMeansEngine.vb:207-218 | Owl.Learning/Clustering/KMeansEngine.vb:430-441
D4 · Code Duplication · Duplicated block (11 lines × 2) · ×1
  • Duplicated block (11 lines × 2) Owl.GH/Params/Param_OwlFiles.vb:45 — Owl.GH/Params/Param_OwlFiles.vb:45-55 | Owl.GH/Params/Param_OwlFiles.vb:103-113
D4 · Code Duplication · Duplicated block (8 lines × 2) · ×1
  • Duplicated block (8 lines × 2) Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:223 — Owl.Accord.GH/Components/Display/NetworkPreview_Attributes.vb:223-230 | Owl.GH/Components/Owl/Obsolete/TensorSetPreview_Attributes.vb:166-173
D4 · Code Duplication · Duplicated block (6 lines × 2) · ×1
  • Duplicated block (6 lines × 2) Owl.GH/Params/Param_OwlFiles.vb:19 — Owl.GH/Params/Param_OwlFiles.vb:19-24 | Owl.GH/Params/Param_OwlFiles.vb:77-82
D4 · Code Duplication · Duplicated block (5 lines × 5) · ×1
  • Duplicated block (5 lines × 5) Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb:35 — Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb:35-39 | Owl.Accord.GH/Components/Backpropagation/BackpropThreaded.vb:40-44 | Owl.Accord.GH/Components/Unsupervised/TSNE.vb:38-42 | Owl.Accord.GH/Components/Unsupervised/TSNE.vb:116-120 | Owl.GH/Components/Owl.Learning/Reinforcement/1/ConstructQLearn.vb:27-31
D4 · Code Duplication · Duplicated block (5 lines × 3) · ×1
  • Duplicated block (5 lines × 3) Owl.Accord.GH/Components/Backpropagation/BackOwl.vb:30 — Owl.Accord.GH/Components/Backpropagation/BackOwl.vb:30-34 | Owl.Accord.GH/Components/Backpropagation/BackpropLearning.vb:33-37 | Owl.Accord.GH/Components/Backpropagation/BackpropThreaded.vb:38-42
D5 · Coupling · Off the main sequence · ×1
  • Off the main sequence: Owl.Core — Owl.Core: abstractness 0.10, instability 0.00, distance 0.90 — zone of pain — concrete and heavily depended-on, so it's rigid to change.
Recommendation — 15 finding(s)
D18 · Solution Shape · Shell project · ×8
  • Shell project: Owl.Core Owl.Core/Owl.Core.vbproj — `Owl.Core` 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: Owl.GH.Common Owl.GH.Common/Owl.GH.Common.vbproj — `Owl.GH.Common` 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: Owl.Learning Owl.Learning/Owl.Learning.vbproj — `Owl.Learning` 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: Owl.Accord.Extensions Owl.Accord.Extensions/Owl.Accord.Extensions.vbproj — `Owl.Accord.Extensions` 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: Owl.Accord.GH Owl.Accord.GH/Owl.Accord.GH.vbproj — `Owl.Accord.GH` 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: Owl.Accord.GH.Common Owl.Accord.GH.Common/Owl.Accord.GH.Common.vbproj — `Owl.Accord.GH.Common` 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: Owl.GH Owl.GH/Owl.GH.vbproj — `Owl.GH` 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: Owl.GH.Networking Owl.GH.Networking/Owl.GH.Networking.vbproj — `Owl.GH.Networking` contributes only 0 significant line(s) — an empty/placeholder project is structural noise. Remove it or fold its contents into a real project.
D11 · Test Reliability · Test reliability not included · ×1
  • Test reliability not included — No test projects found, so reliability couldn't be assessed.
D21 · Naming Consistency · The concept of counting inputs is named 'InputsCount' in some classes but 'InputsCount' in others. However, looking at the list, all three use 'InputsCount'. Wait, let me re-read carefully. Ah, there is a parameter named 'inputs' vs 'input' vs 'input' vs 'output' vs 'desiredOutput'. Let's look for naming inconsistencies of the same concept. · ×1
  • The concept of counting inputs is named 'InputsCount' in some classes but 'InputsCount' in others. However, looking at the list, all three use 'InputsCount'. Wait, let me re-read carefully. Ah, there is a parameter named 'inputs' vs 'input' vs 'input' vs 'output' vs 'desiredOutput'. Let's look for naming inconsistencies of the same concept. — Ensure consistent naming for input/output parameters and properties. (symbols: Owl.Learning.Neuro.ActivationNetwork.InputsCount, Owl.Learning.Neuro.ActivationLayer.InputsCount, Owl.Learning.Neuro.ActivationNeuron.InputsCount)
D21 · Naming Consistency · Inconsistency in naming the collection of components · ×1
  • Inconsistency in naming the collection of components: 'Neurons' for a layer, 'Layers' for a network. While distinct, the pattern of pluralizing the component name is consistent. However, there is a parameter naming inconsistency: 'input' vs 'inputs' vs 'desiredOutput' vs 'output'. Specifically, 'input' (singular) is used in BackPropagationLearning.CalculateError and ActivationNeuron.Compute, while 'inputs' (plural) is used in BackPropagationLearning.Run and ActivationLayer.Compute. This is a minor inconsistency in parameter naming for the same concept (the input data). — Standardize parameter names for input data to be consistent (e.g., always 'input' or always 'inputs'). (symbols: Owl.Learning.Neuro.ActivationNeuron.Weights, Owl.Learning.Neuro.ActivationNeuron.Threshold, Owl.Learning.Neuro.ActivationNeuron.Output, Owl.Learning.Neuro.ActivationLayer.Neurons, Owl.Learning.Neuro.ActivationNetwork.Layers, Owl.Learning.Neuro.ActivationNetwork.Output, Owl.Learning.Neuro.ActivationNetwork.InputsCount, Owl.Learning.Neuro.ActivationNetwork.ActivationFunction)
D23 · Boundary Type-Coupling · Bounded contexts not declared · ×1
  • Bounded contexts not declared — At 13482 LoC spread over 9 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.
D24 · Comment Value · redundant comment · ×1
  • redundant comment Owl.Learning.Neuro/ActivationLayer.cs:7 — "AForge Neural Net Library" — delete - the namespace name is self-describing
D34 · Knowledge Freshness · Further orphaned files (smaller) · ×1
  • Further orphaned files (smaller) — 1 smaller file(s) also have no living knowledge — folded into the freshness score and metrics rather than listed individually (1 orphaned of 1 analysed files in total).
D9 · Test Distribution · No tests found · ×1
  • No tests found — No test projects found in the repository.
Info — 10 finding(s)
D19 · Documentation Quality · XML-doc coverage · ×8
  • XML-doc coverage: Owl.Core Owl.Core/Owl.Core.vbproj — Owl.Core: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.GH.Common Owl.GH.Common/Owl.GH.Common.vbproj — Owl.GH.Common: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.Learning Owl.Learning/Owl.Learning.vbproj — Owl.Learning: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.Accord.Extensions Owl.Accord.Extensions/Owl.Accord.Extensions.vbproj — Owl.Accord.Extensions: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.Accord.GH Owl.Accord.GH/Owl.Accord.GH.vbproj — Owl.Accord.GH: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.Accord.GH.Common Owl.Accord.GH.Common/Owl.Accord.GH.Common.vbproj — Owl.Accord.GH.Common: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.GH Owl.GH/Owl.GH.vbproj — Owl.GH: 100 % XML-doc coverage (0/0).
  • XML-doc coverage: Owl.GH.Networking Owl.GH.Networking/Owl.GH.Networking.vbproj — Owl.GH.Networking: 100 % XML-doc coverage (0/0).
D18 · Solution Shape · Build did not complete in the analyzer · ×1
  • Build did not complete in the analyzer — `dotnet build` reported 9 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.

DimensionToolVersionCommandFindingsRaw output
D28 · Secrets (history)gitleaks—gitleaks detect --no-banner --report-format json --report-path /dev/stdout --exit-code 0 --source .0artifacts/raw/gitleaks-history.json
D29 · Static Analysis (SAST)semgrep—semgrep --config /opt/semgrep-rules/security-audit.yml --config /opt/semgrep-rules/owasp-top-ten.yml --json --quiet --timeout 0 --metrics off .0artifacts/raw/semgrep.json
D30 · Dependency Vulnerabilitiesdotnet—dotnet list Owl.sln package --vulnerable --include-transitive --format json0artifacts/raw/dotnet-vulnerable.json
D31 · IaC & Container Securitytrivy—trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.0—
D32 · Data Compliance (PII/GDPR)semgrep—semgrep: not applicable — No PII/GDPR ruleset is bundled (the public p/gdpr semgrep pack was retired) — data compliance is not assessed in this scan.0—
D33 · JS/npm Dependency Vulnerabilitiestrivy—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.0—
D36 · Supply-chain Provenance & Signingprovenance—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.0—
D37 · Vulnerability-disclosure Policydisclosure—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.0—
D38 · OSV Dependency Vulnerabilitiesosv-scanner—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-943a-728f-a58b-7f76db3db12f · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.

Issues: 2 · Warnings: 58 · Recommendations: 15 · Info: 10 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 08-08-2026 @ 00:20 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.

⬇ Findings, MITRE CWE-tagged .sarif⬇ Health changelog .md