Public report — CASSYS, published 16 Aug 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
61findings with an exact file:lineof 70 — the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
43/100dimensions across the health lenses7816 LoC · 1 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.
CanadianSolar/CASSYS 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 Architecture (100%) — the structure is clean and changes stay contained. Security (100%) is solid too.
The area that most needs attention is Readiness (24%) — 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: Small (~7,816 production lines); rebuilding it from scratch would take roughly ~0.2 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.
How the score is built — each lens's share of the headlineWidth is the lens's weight in the worst-heaviest fold (the weakest area pulls hardest); colour is that lens's own band. A lens fixes the score in proportion to its width.
This codebase represents roughly ~0.2 person-years of build effort (about ~€29,000 to rebuild). Its weakest lens is Readiness at 24% — the part of that asset most exposed by the findings below.
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.
Value concentrated against a weak lens · High · Value at risk
This is a Small asset (~0.2 person-years to rebuild), and its weakest lens is Readiness at 24%. The operational and business risk on an asset this size concentrates there — that's where remediation buys the most protection.
→ Direct remediation budget at Readiness first — highest risk-reduction per euro on an asset this size.
Highest-leverage move · Medium · Leverage
Of everything flagged, the best return on effort is: Add a 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.
A velocity tax on every change · Medium · Economics
The code-quality signals (complexity, duplication, cohesion) average 6.6/10, which acts as a tax on every change in the weaker areas: modifications there plausibly cost on the order of 3–8% more than in clean code, and the tax compounds as the codebase grows. (A modelled estimate, not a measured fact.)
Evidence: D1/D2/D4/D6 code quality: averaging 6.6/10 across the code-quality signals actually measured
→ Pay it down where churn is highest — the hotspots — not everywhere; that's where the tax is actually paid.
At a glance — Code Health · 83% · Adequate · gated by D2
Top priorities: Add a CI workflow that builds and runs the test suite on every push/PR; Resolve the 1 No automated tests finding(s) in Code Coverage; Resolve the 1 No tests found finding(s) in Test Distribution.
Ranked by impact ÷ effort. "Helps" is the estimated gain on the 0–100 health score.
Do this
Helps
Effort
Dimension
Resolve the 1 No automated tests finding(s) in Code Coverage.
For more than a log file, an `ActivitySource`/`EventSource` the user can switch on gives you a structured trace to attach to a bug report. A health-check endpoint does not apply here: nothing orchestrates or load-balances a binary the user launches.
Record significant decisions one document per decision — dated, stating the context, the decision and its consequences — and keep them together wherever your design docs already live (a conventional `docs/adr/` tree, with each file named `NNNN-title` in whatever markup those docs already use, is the most discoverable form).
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. 41 of 43 evaluated dimensions are computed purely by tools and static analysis (confidence 1.0); 2 documentation/naming judgement(s) are LLM-assisted and labelled advisory. Overall confidence is 0.5 — 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 — 43 dimensions across the health lenses
Each chip is a dimension scored from real signals across architecture, testing, dependencies, security & compliance, documentation, git-history and code quality — in one coherent pass. A surface report typically covers a handful.
How to trust any code-health report — three questions
Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line — never an absolute scratch path. Here, 61 of 70 do; the remainder are repo-wide signals — a dimension-level measurement, not a single line. (Every path in this report is repo-relative by construction: paths are normalized at the producer and the report is rejected if any rooted path leaks through.)
Is there a tool behind the number? Every score below names the method that produced it — Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled · advisory — not a narrative.
Does re-running give the same result? Run it again on the same commit and the score — and this report, byte for byte — is identical. A report whose numbers move between runs is describing the run, not the code.
This report answers yes to all three. That's the bar to hold any assessment to.
Tools & methods
The actual versions used this run (captured at analysis time) — re-run on the same commit for the identical score.
Method
Backs
Version
Evaluator
Roslyn static analysis
Complexity, cohesion, coupling, dead code, API surface, layering
What ran differently this time — a tool absent, degraded, or that fell back to an estimate. Named openly, not folded silently into the scores. A degraded run also records its exact cause in diagnostics.md.
D21 Naming Consistency — LLM provider failed — The model provider returned an unusable result, so this LLM-assisted dimension fell back to a measurement gap (confidence 0) rather than a penalty. Re-run with a reachable provider to score it.
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 (scaffolded migrations, designer/codegen output, protobuf/OpenAPI stubs, model snapshots) is EXCLUDED — its repetition is the tool's, not the team's — so the score reflects hand-written duplication only.
D5 Coupling: Coupling is measured between projects/assemblies — runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic — it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D8 Code Coverage: Coverage is measured by building and running the test suite 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.
D17 Explicit Debt: Acknowledged-debt signals (TODO/FIXME, suppressions, dead code) are textual — undocumented debt that nobody marked, and debt that lives in design rather than annotations, is invisible. Committed machine-written code (scaffolded migrations, designer/codegen output, generated stubs) is excluded — it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment — a build that needs a private feed, a specific SDK, or a generated file absent from the repo can read as broken when it is merely unreproducible here.
D19 Documentation Quality: Documentation quality is judged by an LLM over a bounded sample of docs — it reads what is written, not whether the docs match the running system, and it is advisory, not a measurement.
D20 ADR Quality: ADR quality is an LLM read of the decision records present — it cannot know about decisions made and never recorded, and its verdict is sampled and advisory.
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").
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, D20, D24, M4 (model: Local LLM). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) — D25 sets the ADR-conformance fraction over sampled code, D22 judges API accuracy over a sample. These are sampled and advisory by design: they vary at the margins between runs and are never a deterministic measurement. Every other score in this report is tool-computed at confidence 1.0.
What it measures: How tangled the control flow is — methods with many branches are hard to test and change.
Method: Cyclomatic complexity per method (1 + decision points), computed exhaustively across production source; test projects separated by convention. Deterministic.
14 method(s) exceeded the cyclomatic complexity threshold of 15; the worst was Tracker.Calculate at 45. A further 1 method(s) were over the threshold but excluded as flat dispatchers (a long switch/match over independent cases: many branches, almost no nesting), the largest being ReadFarmSettings.GetAttribute at 22 — they are counted neither in the figure above nor in this dimension's score.
+ 9 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 Tracker.Calculate (cyclomatic 45) finding(s) in Cyclomatic Complexity — start with Tracker.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 Splitter.Calculate (cyclomatic 36) finding(s) in Cyclomatic Complexity — start with Splitter.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 ReadFarmSettings.GetInnerText (cyclomatic 32) finding(s) in Cyclomatic Complexity — start with ReadFarmSettings.cs. — One of this dimension's main actionable groups (1 warning-level).
Stand up a CI pipeline, then gate Cyclomatic Complexity in it to reach Verified (currently Documented). — This repository has no CI pipeline, so there is nothing to add a gate to yet — the pipeline comes first. Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d1_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: How hard the code is for a person to follow, beyond raw branching.
Method: Cognitive complexity per method (Sonar-style nesting-penalized score), computed exhaustively over production code, excluding test projects. Deterministic.
+ 13 more group(s) — more in Appendix A; the complete list is findings.md.
What to do
Resolve the 1 Tracker.Calculate (cognitive 104) finding(s) in Cognitive Complexity — start with Tracker.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 GroundShading.CalcGroundShading (cognitive 103) finding(s) in Cognitive Complexity — start with GroundShading.cs. — One of this dimension's main actionable groups (1 warning-level).
Resolve the 1 BackTilter.Calculate (cognitive 97) finding(s) in Cognitive Complexity — start with BackTilter.cs. — One of this dimension's main actionable groups (1 warning-level).
Stand up a CI pipeline, then gate Cognitive Complexity in it to reach Verified (currently Documented). — This repository has no CI pipeline, so there is nothing to add a gate to yet — the pipeline comes first. Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d2_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D3 · God Classes7.5 / 10Strong✓ Tool-verified
What it measures: Over-large classes that try to do too much ("god classes").
Method: God-class detection by line and method-count thresholds per logical type (partial classes unified), filtered for generated code and registration/contract false positives. Deterministic.
Resolve the 4 MethodTooLong finding(s) in God Classes — start with BackTilter.cs, Tracker.cs, GroundShading.cs. — One of this dimension's main actionable groups (4 warning-level).
Resolve the 1 ClassTooLong finding(s) in God Classes — start with PVArray.cs. — One of this dimension's main actionable groups (1 warning-level).
Stand up a CI pipeline, then gate God Classes in it to reach Verified (currently Documented). — This repository has no CI pipeline, so there is nothing to add a gate to yet — the pipeline comes first. Hardens enforcement from Documented toward Prevented — provenance only; does not change the score.
Detailed fixes: d3_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Copy-pasted code that should be shared instead.
Method: Code duplication via token-stream sliding windows with type-aware normalization (locals masked, type names preserved), density-scored per KLoC of production code. Deterministic.
+ 2 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.
Do you agree with this assessment?
D5 · Coupling10.0 / 10Exemplary✓ Tool-verified
What it measures: Whether volatile projects sit underneath others that depend on them (so their churn ripples upward), and whether project dependencies form cycles. A widely-depended-on but stable shared/kernel project is healthy, not penalised.
Method: Dependency cycles via elementary-DFS over real .csproj references, plus Martin instability (afferent/efferent) per project. Exhaustive over the reference graph, deterministic.
Coverage: Exhaustive · type-level: afferent/efferent coupling + cycles computed over every production type — the population is all types, not a name convention.
What it measures: Whether a class's methods are focused on a single responsibility.
Method: LCOM4 cohesion per production class with at least two methods: connected components of methods sharing state or calls, computed syntactically. Deterministic, not a proxy.
Coverage: Exhaustive · type-level: LCOM4 cohesion computed over every production class — the population is all types, not a name convention.
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.
No automated tests — no test code was found in this repository.
No automated tests
What to do
Resolve the 1 No automated tests finding(s) in Code Coverage. — One of this dimension's main actionable groups (1 issue-level).
Stand up a CI pipeline, then gate Code Coverage in it to reach Verified (currently Documented). — This repository has no CI pipeline, so there is nothing to add a gate to yet — the pipeline comes first. 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.
Do you agree with this assessment?
D9 · Test Distribution0.0 / 10Critical✓ Tool-verified
What it measures: Whether the test suite has a healthy mix of unit / integration / end-to-end tests.
Method: Test projects classified (Unit/Integration/BDD/E2E) from compiled metadata; test methods counted exhaustively across projects with placement-agnostic disk fallback. Deterministic.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
What it measures: Whether any secrets (keys, tokens, passwords) have leaked into the code.
Method: In-process native secret scanner (entropy plus signature patterns) across all tracked files; no external tool. A clean result is a measured 10, not no-data zero. Deterministic.
What it measures: Files that change often and are also complex — the riskiest hotspots.
Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.
What it measures: 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.
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.
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.
CASSYS has a single README file that is well written for its purpose: it describes the software (version, goals), the two main components (Excel interface and C# engine), installation via an installer link, and links to the Canadian Solar O&M Inc. website. It also begins outlining documentation, licensing, and future work before being cut by the scanner clip marker. The README is clear but thin on architecture/design docs and XML doc coverage for a simulation tool.
Improve Documentation Quality — currently 5.0/10. — CASSYS has a single README file that is well written for its purpose: it describes the software (version, goals), the two main components (Excel interface and C# engine), installation via an installer link, and links to the Canadian Solar O&M Inc. website. It also begins outlining documentation, licensing, and future work before being cut by the scanner clip marker. The README is clear but thin on architecture/design docs and XML doc coverage for a simulation tool.
Detailed fixes: d19_recommendation.md · top locations in Appendix A, every location in findings.md.
What it measures: Whether architecture decisions are recorded well (context, decision, consequences).
Method: Per-ADR judgment by language model at low temperature with two-pass stability; confidence is share of ADRs evaluated; enforcement-field presence detected deterministically. Advisory.
Resolve the 1 No ADRs found finding(s) in ADR Quality. — One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d20_recommendation.md · top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D24 · Comment Value / 10Exemplary◐ 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.
What it measures: Whether any secrets were ever committed — scanned across the full git history, not just now.
Method: Git-history secret scan via gitleaks detect over full history in an isolated checkout; each match flagged High. Exhaustive; degrades cleanly when tool absent.
What it measures: Real static-analysis (SAST) findings — likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep across the repo using the pinned, image-baked p/security-audit + p/owasp-top-ten rulesets (no scan-time registry fetch); severity rules (ERROR/WARNING/INFO) map to a full-band severity-weighted score. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files — exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
What it measures: Whether 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.
25 of 25 significant source file(s) are orphaned — their living knowledge has decayed to nothing, so no one currently understands them. The largest is CASSYS Engine/PVArray.cs.
Largest orphaned file · ×3CASSYS Engine/PVArray.cs
Dormant codebase
What to do
Resolve the 3 Largest orphaned file finding(s) in Knowledge Freshness — start with PVArray.cs, GridConnectedSystem.cs, ReadFarmSettings.cs. — One of this dimension's main actionable groups (3 recommendation-level).
Resolve the 1 Dormant codebase 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.
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.
Other · Architecture — How the codebase splits by code ROLE — domain, application, infrastructure, test, generated. The significance map behind the knowledge/coupling weighting, and a DDD signal in its own right: a thin domain core under fat infrastructure is the anemic-domain smell, quantified.
Method: Roslyn line-count by code ROLE: every source file classified Domain/Application/Infrastructure/Test/Generated by namespace + path convention (the shared CodeRoleClassifier), then significant lines summed per role. Deterministic; the advisory score is the business-logic (domain+application) share of production code.
Coverage: Population: ALL source files, each bucketed into ONE of five roles (Domain/Application/Infrastructure/Test/Generated) by namespace + path convention — a file whose layer isn't named in the convention falls to Application (the neutral default), and the split is line-count, not semantic depth or business value.
What to do
The domain core is a small share of production code — check that business logic isn't leaking into the application/infrastructure layers (a thin domain is the anemic-domain smell).
Other · Architecture — Whether the project-reference graph is acyclic (cycles block independent build/deploy and signal eroding boundaries).
Method: Project reference cycles via elementary-DFS over real .csproj references, using the engine shared with D5/D7; cyclic versus acyclic. Exhaustive, deterministic.
Other · Architecture — Whether dependencies point inward (Domain ← Application ← Infrastructure/Web) — the clean-architecture dependency rule, checked across the project graph.
Method: Layer violations by name-segment inference (Domain/Core to Application to Infrastructure/Web) over the project-reference graph. Exhaustive over all projects, deterministic.
Other · Architecture — Whether the codebase has a recognisable, scale-appropriate structure (a named architectural style, or modular enough for its size) rather than being an ad-hoc ball of mud.
Method: Roslyn plus csproj analysis: architecture style detection (DDD, clean, vertical-slice, CQRS) and structure fitness for repo size. Deterministic.
Other · Code Health — Unreviewed-generation residue: shipped members still throwing NotImplementedException, and placeholder string literals left in non-test, non-generated code. Scored as a quality signature, never as a claim about authorship.
Method: Roslyn syntax scan: NotImplementedException throws and placeholder string literals in non-test, non-generated shipped code. Deterministic, code-shape signature.
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.
A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers). (×7) — BackTilter.cs:390, GridConnectedSystem.cs:429, GroundShading.cs:205, …
What to do
Clear the softer debt: remove commented-out code and dead branches, re-enable or delete skipped tests, and replace blanket warning suppressions with targeted ones.
Maturity · Maturity — Whether the repo and its projects have a README, and whether it's substantive and current.
Method: Filesystem scan: README presence, word count, and headings for depth; git history for staleness. Exhaustive across root and project dirs, deterministic.
What to do
Add a 'Testing' section to the root README — how to run the test suite.
Add an 'Architecture' / 'How it works' section to the root README — the high-level shape.
Add a README to the 1 of 1 project(s) that lack one — worth up to 2 pts.
Maturity · Maturity — Whether key decisions (ADRs) and the high-level shape (C4/diagrams) are written down.
Method: Filesystem scan: ADR folder/naming conventions or content, plus Mermaid/PlantUML/C4/architecture.md discovery. Exhaustive, deterministic.
No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.
No C4/PlantUML/Mermaid diagram or architecture.md — the high-level shape isn't documented.
What to do
Record significant decisions one document per decision — dated, stating the context, the decision and its consequences — and keep them together wherever your design docs already live (a conventional `docs/adr/` tree, with each file named `NNNN-title` in whatever markup those docs already use, is the most discoverable form).
Add a C4 context/container diagram (Structurizr, PlantUML or Mermaid) or an architecture.md overview.
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.
No test surface was found — there are no tests here to separate from production code, so the folder question hasn't been reached yet.
What to do
Start a test surface where your build system looks for one (tests/, test/, spec/, or your ecosystem's test source set) — the separation follows from putting the first tests in the right place.
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.
Do you agree with this assessment?
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.
Do you agree with this assessment?
P2 · Observability7.0 / 10Strong✓ Tool-verified
Readiness · Readiness — Whether the code is diagnosable in production — structured logging, tracing/metrics, health checks.
For more than a log file, an `ActivitySource`/`EventSource` the user can switch on gives you a structured trace to attach to a bug report. A health-check endpoint does not apply here: nothing orchestrates or load-balances a binary the user launches.
Readiness · Readiness — Whether SAST, secret/dependency scanning and performance benchmarking are wired in (presence, not runtime).
Method: Filesystem scan: SAST configuration, dependency-update automation, secret scanning, and a benchmark harness or benchmark step — in this repository's own ecosystem. Exhaustive, deterministic.
No static application security testing detected. For this repository's stack, add CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package (or `semgrep --config=auto`, which runs on any language) — this repository has no CI pipeline yet, so run it locally to clear the existing findings, then make it a step of the first workflow you add so a regression fails the build.
What to do
Run what this repository's stack ships: CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package — or `semgrep --config=auto`, which runs on any language — locally for now, since there is no CI pipeline here yet, and as a step of the first workflow you add so a security regression fails the build instead of landing.
Enable Dependabot/Renovate or a dependency-review gate.
Add gitleaks/trufflehog in CI to block PRs that introduce committed secrets.
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.
Other · Code Health — Whether any branch is dead by construction — a switch arm whose label can never equal a case-normalised subject, or an `else if` whose predicate the arm above has already swallowed.
Method: Roslyn syntax + semantics: switch labels compared against the subject's own case normaliser, and if/else-if chains checked for a literal an earlier arm's containment test already swallows. Deterministic, provable per finding. Advisory.
Do you agree with this assessment?
X13 · Undrained process stream10.0 / 10Exemplary○ Nothing flagged
Other · Code Health — Whether a child process that has BOTH standard streams redirected drains both — reading one to the end while the other is never read deadlocks once the child fills the unread pipe.
Method: Roslyn syntax + semantics: ProcessStartInfo launches with both streams redirected, checked for a drain of each stream across the enclosing type. Deterministic, provable per finding. Advisory.
Other · Security — Whether a hand-rolled public/private IP check can be walked past — a method that unwraps IPv4-mapped IPv6 but returns the opposite verdict for the same host written as IPv4-compatible, 6to4 or NAT64.
Method: Roslyn syntax + semantics: methods that unwrap IPv4-mapped IPv6 and hand-roll IPv4 range carve-outs, checked for whether the IPv6 branch also accounts for the IPv4-compatible, 6to4 and NAT64 embeddings. Deterministic, provable per finding. Advisory.
Do you agree with this assessment?
X15 · Unvalidated length from an untrusted reader10.0 / 10Exemplary○ Nothing flagged
Other · Security — Whether a length read out of the stream being parsed is bounded before it is allocated or read — an unchecked count taken from the input lets the input choose the allocation.
Method: Roslyn syntax + semantics: integer lengths read from a BinaryReader and spent on a bulk read or an array allocation, checked for any comparison or bounding call on the value anywhere in the method. Deterministic, provable per finding. Advisory.
Other · Code Health — Whether a loop that shortens a string until it fits a length budget has a floor — one with none grinds the value down to the empty string, or past it into a negative-length `Substring`.
Method: Roslyn syntax + semantics: while/do loops whose body's only effect on a string is to drop its last character, checked for whether anything — a direct comparison on the length, a body guard, a break — bounds that length below. Deterministic, provable per finding. Advisory.
Do you agree with this assessment?
X17 · Uncapped recursion over a caller-supplied document10.0 / 10Exemplary○ Nothing flagged
Other · Security — Whether a walk that recurses through a JSON/XML tree handed in by its caller bounds how deep it will go — an uncapped walk lets the document's nesting choose the stack depth, and the resulting StackOverflowException cannot be caught.
Method: Roslyn syntax + semantics: methods that take a JSON/XML document node and call themselves with a child of it, reachable from an externally-callable member of the same type that accepts a document, checked for any depth parameter, descent counter or threaded arithmetic anywhere in the walk. Deterministic, provable per finding. Advisory.
Other · Code Health — Whether a type's disposal matches what it OWNS — releasing what it created, leaving alone what it was handed, and not declaring a finalizer for state that has nothing unmanaged to finalize.
Method: Roslyn syntax + semantics: every assignment to a disposable field is read to decide whether the type CREATED the value or was handed it, and the type's disposal is checked against that answer — an injected interface it disposes, a value it constructed and never releases, a finalizer on a type holding nothing unmanaged, and a disposable local whose every reference is a plain member read. Deterministic, provable per finding. Advisory.
Other · Code Health — Whether a method that temporarily changes state belonging to the whole process — the working directory, an environment variable — puts it back on EVERY path: a restore reached only when nothing throws leaks the change to the rest of the process.
Method: Roslyn syntax + semantics: method bodies that write the process working directory or an environment variable and write it back in the same body, checked for whether that restore sits in a `finally`/`catch` or only on the straight-line path. Deterministic, provable per finding. Advisory.
Do you agree with this assessment?
Reference — by lens
The score is the rank-weighted fold of these lenses (worst-heaviest), each including its meta-dimensions; a lens with a Critical contributor is capped at Fair (its band reads "gated by …") and is never the strongest area however high its average.
Not included — 57 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 were found in the analyzed repository 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
D16 Bus Factor — dormant codebase — no living knowledge left to concentrate
D21 Naming Consistency — LLM evaluation failed
D22 Internal API Consistency — No exposed public API
D23 Boundary Type-Coupling — At only 7816 LoC in a single project the codebase is trivially small despite having no bounded contexts declared, so boundaries are not needed.
D25 ADR Conformance — no ADRs to check
D27 Navigability — symbol resolution incomplete — navigability not assessed
D30 Dependency Vulnerabilities — `dotnet list package --vulnerable` could not read this solution's dependency graph — it reported an error for at least one project and returned no package data at all (typically a packages.config / non-PackageReference project, which the command cannot read; classic .NET Framework projects are packages.config by default). No packages could be enumerated, so there was nothing to scan for NuGet CVEs — excluded rather than scored, because an unreadable dependency graph is not a clean one; migrate the project(s) to PackageReference to enable this scan
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-handling patterns detected (p/gdpr ruleset) — no data-compliance surface to assess.
D33 JS/npm Dependency Vulnerabilities — No JS/npm manifest or lockfile found outside build output (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/.forgejo/.gitea workflows, .gitlab-ci.yml, azure-pipelines*.yml, .pipelines/, .vsts-ci/, Jenkinsfile, .circleci); there is no build to attest provenance for.
D37 Vulnerability-disclosure Policy — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
D38 OSV Dependency Vulnerabilities — No supported non-.NET dependency lockfile found outside build output (npm package-lock/yarn/pnpm/bun, Go go.mod, Rust Cargo.lock, Maven pom.xml, Gradle lockfiles, Python requirements.txt/poetry.lock/Pipfile.lock/pdm.lock, PHP composer.lock, Ruby Gemfile.lock, Elixir mix.lock, Dart pubspec.lock, Swift Package.resolved); nothing for OSV to scan. A NuGet-only repo stays NotApplicable — .NET CVEs are D30's domain.
D39 IL Efficiency — The target did not build, so no IL was available to measure.
D40 Network Egress Confinement — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
D41 Kernel & Syscall Confinement — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
D42 Runtime Threat Enforcement — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
D7 Architectural Integrity — no checkable ADRs and no dependency cycles — architectural integrity not assessed
DM1 Domain Modelling — not scored — this repository shows none of the 3 signals this check looks for
ED1 Event-Driven — not scored — this repository shows none of the 3 signals this check looks for
ED5 Idempotency — no mutating command handlers or message consumers detected — idempotency check not applicable
ES1 Event Sourcing — not scored — this repository shows none of the 3 signals this check looks for
P12 CI test-gate honesty — no CI workflow found
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 — produce a coverage report in a standard format (Cobertura — `dotnet test --collect:"XPlat Code Coverage"` with a `coverlet.collector` PackageReference) into the repo working tree before the scan — a CI step is the usual place, since the artefact is commonly gitignored, or wire coverage collection into 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.
X10 Duplicated predicate — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
X6 Hand-rolled structured-format parsing — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
X7 Silent fallback defaults — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
X9 Subsumed condition operand — Reported, not scored — this card publishes what it found rather than grading it. Its content is the findings and the key metric above.
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.
WriteOnlyPrivateField CASSYS Engine/GridConnectedSystem.cs:42— private HorizonShading SimHorizon — assigned 1 time(s), read never — this field is written and never read anywhere its type can be reached from, so the state it keeps answers no question: every assignment to it computes a value that nothing observes, on every instance, for the lifetime of each one. It reads as a flag the code branches on, and nothing branches on it. Delete the field and its assignments — or, if the value was MEANT to be consulted, the missing read is the defect this row is pointing at, and the branch that should have depended on it is not there.
WriteOnlyPrivateField CASSYS Engine/PVArray.cs:62— private double itsSubArrayNum — assigned 1 time(s), read never — this field is written and never read anywhere its type can be reached from, so the state it keeps answers no question: every assignment to it computes a value that nothing observes, on every instance, for the lifetime of each one. It reads as a flag the code branches on, and nothing branches on it. Delete the field and its assignments — or, if the value was MEANT to be consulted, the missing read is the defect this row is pointing at, and the branch that should have depended on it is not there.
WriteOnlyPrivateField CASSYS Engine/Shading.cs:38— private double itsCollTilt — assigned 2 time(s), read never — this field is written and never read anywhere its type can be reached from, so the state it keeps answers no question: every assignment to it computes a value that nothing observes, on every instance, for the lifetime of each one. It reads as a flag the code branches on, and nothing branches on it. Delete the field and its assignments — or, if the value was MEANT to be consulted, the missing read is the defect this row is pointing at, and the branch that should have depended on it is not there.
WriteOnlyPrivateField CASSYS Engine/Simulation.cs:40— private SimMeteo SimMet — assigned 1 time(s), read never — this field is written and never read anywhere its type can be reached from, so the state it keeps answers no question: every assignment to it computes a value that nothing observes, on every instance, for the lifetime of each one. It reads as a flag the code branches on, and nothing branches on it. Delete the field and its assignments — or, if the value was MEANT to be consulted, the missing read is the defect this row is pointing at, and the branch that should have depended on it is not there.
TodoComment CASSYS Engine/GroundShading.cs:388— // TODO: improve accuracy (especially for n < 100) by setting 1 only if > 50% of segment is shaded — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment CASSYS Engine/GroundShading.cs:430— // TODO: improve accuracy (especially for n < 100) by setting 1 only if > 50% of segment is shaded — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment CASSYS Engine/GroundShading.cs:527— // TODO: improve accuracy (especially for n < 100) by setting 1 only if > 50% of segment is shaded — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
TodoComment CASSYS Engine/Sun.cs:154— //itsSurfaceSlope = Util.DTOR * double.Parse(ReadFarmSettings.GetInnerText("O&S", "PlaneTilt")); TODO: Re-evaluate. — source code is not a task system: move the work to your tracker and leave a reference instead (e.g. `// REF: #123`), so the task is planned where tasks live and the ticket links back to the code.
MethodTooLong: BackTilter.Calculate CASSYS Engine/BackTilter.cs:159— MethodTooLong — Calculate runs 119 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: Tracker.Calculate CASSYS Engine/Tracker.cs:119— MethodTooLong — Calculate runs 115 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: GroundShading.CalcGroundShading CASSYS Engine/GroundShading.cs:317— MethodTooLong — CalcGroundShading runs 106 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
MethodTooLong: Simulation.Simulate CASSYS Engine/Simulation.cs:54— MethodTooLong — Simulate runs 104 significant lines (blank, comment-only and punctuation-only lines excluded) in one body. This is length, not branching: a long straight-line body scores low on complexity and is still read whole to change any part of it, so the complexity numbers beside this row neither confirm nor excuse it. To reduce it, extract each cohesive step of the body — the runs of statements that work on the same values and would earn the same name — into its own named unit, and have this one call them in order.
Duplicated block (5 lines × 2) CASSYS Engine/Interpolate.cs:265— CASSYS Engine/Interpolate.cs:265-269 | CASSYS Engine/Interpolate.cs:273-277 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/Interpolate.cs:265` it begins part-way through the construct above it, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (5 lines × 2) CASSYS Engine/PVArray.cs:751— CASSYS Engine/PVArray.cs:751-755 | CASSYS Engine/PVArray.cs:767-771 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Duplicated block (5 lines × 2) CASSYS Engine/RadiationProc.cs:215— CASSYS Engine/RadiationProc.cs:215-219 | CASSYS Engine/RadiationProc.cs:284-288 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/RadiationProc.cs:215` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (10 lines × 2) CASSYS Engine/BackTilter.cs:81— CASSYS Engine/BackTilter.cs:81-90 | CASSYS Engine/GroundShading.cs:76-85 — the copies sit in sibling files of one directory: extract the block into a single shared function in that directory and call it from each site, so a change lands once.
Duplicated block (10 lines × 2) CASSYS Engine/Interpolate.cs:243— CASSYS Engine/Interpolate.cs:243-252 | CASSYS Engine/Interpolate.cs:254-263 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited.
Tracker.Calculate (cyclomatic 45) CASSYS Engine/Tracker.cs:119— Tracker.Calculate has cyclomatic complexity 45 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Splitter.Calculate (cyclomatic 36) CASSYS Engine/Splitter.cs:55— Splitter.Calculate has cyclomatic complexity 36 (threshold 15). To reduce it, name the conditions: bind each compound test to a well-named local or a small predicate function, so the body reads as a sequence of named decisions rather than a chain of operators.
ReadFarmSettings.GetInnerText (cyclomatic 32) CASSYS Engine/ReadFarmSettings.cs:338— ReadFarmSettings.GetInnerText has cyclomatic complexity 32 (threshold 15). To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Where every arm is uniform — the same kind of value, with no behaviour of its own — a table keyed by the case is the shorter form; wherever the arms carry different data or different behaviour, keep them as cases, because collapsing those trades an explicit, reviewable set of cases for nothing.
GroundShading.CalcGroundShading (cyclomatic 30) CASSYS Engine/GroundShading.cs:317— GroundShading.CalcGroundShading has cyclomatic complexity 30 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Simulation.Simulate (cyclomatic 28) CASSYS Engine/Simulation.cs:54— Simulation.Simulate has cyclomatic complexity 28 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
BackTilter.Calculate (cyclomatic 27) CASSYS Engine/BackTilter.cs:159— BackTilter.Calculate has cyclomatic complexity 27 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
ReadFarmSettings.AssignOutputFileSchema (cyclomatic 25) CASSYS Engine/ReadFarmSettings.cs:227— ReadFarmSettings.AssignOutputFileSchema has cyclomatic complexity 25 (threshold 15). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.
GridConnectedSystem.AssignOutputs (cyclomatic 22) CASSYS Engine/GridConnectedSystem.cs:255— GridConnectedSystem.AssignOutputs has cyclomatic complexity 22 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
RadiationProc.Calculate (cyclomatic 20) CASSYS Engine/RadiationProc.cs:47— RadiationProc.Calculate has cyclomatic complexity 20 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
GridConnectedSystem.Calculate (cyclomatic 18) CASSYS Engine/GridConnectedSystem.cs:87— GridConnectedSystem.Calculate has cyclomatic complexity 18 (threshold 15). To reduce it, split the body: these branches sit side by side rather than nested inside one another, so extracting each one on its own would leave a function per branch. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
Shading.Config (cyclomatic 17) CASSYS Engine/Shading.cs:266— Shading.Config has cyclomatic complexity 17 (threshold 15). To reduce it, separate the branches: extract each independent case into its own named function, or replace a long branch ladder over a single value with a data-driven lookup or dispatch table.
PVArray.Config (cyclomatic 16) CASSYS Engine/PVArray.cs:540— PVArray.Config has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
Tilter.GetTiltCompIrradPerez (cyclomatic 16) CASSYS Engine/Tilter.cs:126— Tilter.GetTiltCompIrradPerez has cyclomatic complexity 16 (threshold 15). To reduce it, name the conditions: bind each compound test to a well-named local or a small predicate function, so the body reads as a sequence of named decisions rather than a chain of operators.
Tracker.Config (cyclomatic 16) CASSYS Engine/Tracker.cs:393— Tracker.Config has cyclomatic complexity 16 (threshold 15). To reduce it, separate the cases: extract each independent branch into its own named function, and where the body has guards that only reject input, fold those into early returns at the top.
dormant codebase — no living knowledge left to concentrate — Every one of the 25 significant source file(s) was last meaningfully changed so long ago that no living knowledge remains, so there is no concentration to measure — the bus factor is not scored. This is not a clean bill: nobody currently holds working knowledge of this code (see D34 Knowledge Freshness).
Tracker.Calculate (cognitive 104) CASSYS Engine/Tracker.cs:119— Tracker.Calculate has cognitive complexity 104 (threshold 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.
GroundShading.CalcGroundShading (cognitive 103) CASSYS Engine/GroundShading.cs:317— GroundShading.CalcGroundShading has cognitive complexity 103 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function.
BackTilter.Calculate (cognitive 97) CASSYS Engine/BackTilter.cs:159— BackTilter.Calculate has cognitive complexity 97 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function.
RadiationProc.Calculate (cognitive 54) CASSYS Engine/RadiationProc.cs:47— RadiationProc.Calculate has cognitive complexity 54 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function.
ReadFarmSettings.AssignOutputFileSchema (cognitive 48) CASSYS Engine/ReadFarmSettings.cs:227— ReadFarmSettings.AssignOutputFileSchema has cognitive complexity 48 (threshold 15). To reduce it, break up the iteration: give each loop body a named function, and split a multi-phase loop into one function per phase so no single body carries the whole pipeline.
Simulation.Simulate (cognitive 38) CASSYS Engine/Simulation.cs:54— Simulation.Simulate has cognitive complexity 38 (threshold 15). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
Splitter.Calculate (cognitive 36) CASSYS Engine/Splitter.cs:55— Splitter.Calculate has cognitive complexity 36 (threshold 15). To reduce it, split the body: most of this score is breadth rather than depth — checks laid out side by side rather than stacked — so group the statements between the checks into named steps and move each step into its own function. Some of it IS depth: where a check sits inside another whose only job is to reach it, merge the two into one condition, and where an else follows a branch that already returns, drop the trailing else and let the rest of the body continue at one level.
PVArray.Config (cognitive 33) CASSYS Engine/PVArray.cs:540— PVArray.Config has cognitive complexity 33 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Inverter.ConfigEffCurves (cognitive 22) CASSYS Engine/Inverter.cs:275— Inverter.ConfigEffCurves has cognitive complexity 22 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Shading.GetFrontShadedFraction (cognitive 20) CASSYS Engine/Shading.cs:143— Shading.GetFrontShadedFraction has cognitive complexity 20 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function. This shape REPEATS in the file: one other method here (Shading.GetBackShadedFraction) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.
Shading.GetBackShadedFraction (cognitive 20) CASSYS Engine/Shading.cs:205— Shading.GetBackShadedFraction has cognitive complexity 20 (threshold 15). To reduce it, flatten the nesting: invert conditions into early returns or guard clauses so the happy path stays at one level, and lift the deepest nested block into its own named function. This shape REPEATS in the file: one other method here (Shading.GetFrontShadedFraction) has the same decision points, in the same order, at the same nesting depths — so this is one pattern written twice rather than two separate problems. Splitting this body alone leaves the other exactly as it is. Where these are variations on one operation, the change that clears both is the shared one: lift the common shape into a single routine the variants call, parameterised by whatever genuinely differs between them, and keep in each method only the part that is not shared.
Inverter.GetMPPTStatus (cognitive 17) CASSYS Engine/Inverter.cs:139— Inverter.GetMPPTStatus has cognitive complexity 17 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
ReadFarmSettings.GetInnerText (cognitive 17) CASSYS Engine/ReadFarmSettings.cs:338— ReadFarmSettings.GetInnerText has cognitive complexity 17 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Shading.Config (cognitive 17) CASSYS Engine/Shading.cs:266— Shading.Config has cognitive complexity 17 (threshold 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.
GridConnectedSystem.Calculate (cognitive 16) CASSYS Engine/GridConnectedSystem.cs:87— GridConnectedSystem.Calculate has cognitive complexity 16 (threshold 15). To reduce it, split the body: this score is breadth rather than depth — many checks laid out side by side rather than nested inside one another, so inverting conditions into early returns has nothing left to flatten. Group the statements between the checks into named steps and move each step into its own function, so the body reads as a short sequence of named stages.
SimMeteo.ParseCSVLine (cognitive 16) CASSYS Engine/MetReader.cs:262— SimMeteo.ParseCSVLine has cognitive complexity 16 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
ReadFarmSettings.AssignInputFileSchema (cognitive 16) CASSYS Engine/ReadFarmSettings.cs:153— ReadFarmSettings.AssignInputFileSchema has cognitive complexity 16 (threshold 15). To reduce it, split the body into named stages: move each independent step or branch into its own named function so the body reads as a short sequence of named calls rather than one long body.
Tracker.Config (cognitive 16) CASSYS Engine/Tracker.cs:393— Tracker.Config has cognitive complexity 16 (threshold 15). The drivers above price the dispatch low by construction — a dispatch is charged once however many cases it lists, while each branch inside an arm is charged in full — so most of this count is what the case bodies hold, and the arms are where it can be reduced. To reduce it, keep the dispatch but shrink the arms: move each non-trivial case body into its own named function (or onto the value being matched) so the dispatch reads one line per case, and group related cases into a sub-dispatch. Keep every case explicit, and make the behaviour for cases you do not list a deliberate choice rather than an accident.
ClassTooLong: PVArray CASSYS Engine/PVArray.cs:0— ClassTooLong — 460 significant lines (blank, comment-only and punctuation-only lines excluded), 14 methods. To reduce it, group the members that share the same data into a smaller type of their own and delegate to it, so no single type carries every responsibility.
Duplicated block (27 lines × 2) CASSYS Engine/Tracker.cs:287— CASSYS Engine/Tracker.cs:287-313 | CASSYS Engine/Tracker.cs:319-347 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. The matched lines also transfer control out of the body holding them, which cannot survive a move into a called unit unchanged: have the extracted unit return that decision and let each site act on it.
Duplicated block (25 lines × 2) CASSYS Engine/GroundShading.cs:367— CASSYS Engine/GroundShading.cs:367-392 | CASSYS Engine/GroundShading.cs:409-433 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/GroundShading.cs:367` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that. Note that the copies do not run to the end of the range shown: their LAST lines are different code, not the same code under different names — the matched region ends inside that line. Extract the lines above it, and read the last line of each site separately.
Duplicated block (13 lines × 2) CASSYS Engine/Shading.cs:178— CASSYS Engine/Shading.cs:178-190 | CASSYS Engine/Shading.cs:240-252 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/Shading.cs:178` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (12 lines × 3) CASSYS Engine/Shading.cs:316— CASSYS Engine/Shading.cs:316-327 | CASSYS Engine/Shading.cs:350-361 | CASSYS Engine/Shading.cs:383-394 — all 3 copies are in the same file, so extract the block into one function there and call it from every one of those sites — resolving only two of them leaves the rest to drift apart the first time one is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/Shading.cs:316` it does not close everything it opens, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Duplicated block (11 lines × 2) CASSYS Engine/RadiationProc.cs:228— CASSYS Engine/RadiationProc.cs:228-238 | CASSYS Engine/RadiationProc.cs:297-307 — both copies are in the same file, so extract the block into one function there and call it from each site — the copies drift apart the first time only one of them is edited. Read the line range as the matched WINDOW rather than a finished unit: at `CASSYS Engine/RadiationProc.cs:228` it runs out through the closing brace of the declaration holding it — the window is that declaration's tail, not a fragment that begins part-way through something, so those exact lines cannot be lifted as they stand — widen the region to the smallest complete statement or declaration that contains it, and extract that.
Commented-out code CASSYS Engine/BackTilter.cs:390— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/GridConnectedSystem.cs:429— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/GroundShading.cs:205— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/Inverter.cs:236— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/Inverter.cs:241— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/PVArray.cs:565— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
Commented-out code CASSYS Engine/RadiationProc.cs:296— A line of code has been commented out rather than removed — dead weight that rots and confuses. Delete it (version control remembers).
D34 · Knowledge Freshness· Largest orphaned file · ×3
Largest orphaned file CASSYS Engine/PVArray.cs— One of the largest files with no living knowledge remaining — a reasonable place to start a read-through before the aggregate risk above bites.
Largest orphaned file CASSYS Engine/GridConnectedSystem.cs— One of the largest files with no living knowledge remaining — a reasonable place to start a read-through before the aggregate risk above bites.
Largest orphaned file CASSYS Engine/ReadFarmSettings.cs— One of the largest files with no living knowledge remaining — a reasonable place to start a read-through before the aggregate risk above bites.
D11 · Test Reliability· Test reliability not included · ×1
Test reliability not included — No test suite was found, so reliability couldn't be assessed.
Dormant codebase — 25 of 25 significant files have no living knowledge — the codebase as a whole is dormant, not 25 separate risks. Re-engage owners or document before change.
No tests found — No test suite could be collected — nothing here references a test framework (xUnit, NUnit or MSTest), so there were no discoverable tests to count. Tests written as plain executables or shell/PowerShell harnesses are not collectible this way and are not scored here.
No ADRs — No Architecture Decision Records found — no conventional ADR directory, no numbered `NNNN-title` documents in any markup this check reads, and nothing ADR-shaped by content. Design rationale recorded elsewhere (a design-notes tree, a mailing list, pull-request discussion) is not visible to this check and is not re-findable per decision, so a future maintainer cannot ask why one choice was made and get an answer.
M2 · Architecture documentation· No architecture diagram/doc · ×1
No architecture diagram/doc — No C4/PlantUML/Mermaid diagram or architecture.md — the high-level shape isn't documented.
No tests/ separation — No test surface was found — there are no tests here to separate from production code, so the folder question hasn't been reached yet.
No SAST — No static application security testing detected. For this repository's stack, add CodeQL's csharp pack (it analyses VB.NET too), or a security analyzer package (or `semgrep --config=auto`, which runs on any language) — this repository has no CI pipeline yet, so run it locally to clear the existing findings, then make it a step of the first workflow you add so a regression fails the build.
No changelog — No CHANGELOG/HISTORY/RELEASES file — what shipped when isn't easy to reconstruct for support or audit. (Versioning/tagging makes releases traceable, but a changelog records the what.)
Info — 3 finding(s)
D18 · Solution Shape· Build did not complete in the analyzer · ×1
Build did not complete in the analyzer — `dotnet build` reported 1 error(s) but no C# compiler diagnostic, so this is a build-environment gap rather than a code defect. The usual causes are a project that targets a platform this run cannot build (a Windows-only target framework on a Linux worker) or a build step that shells out to a tool the image does not carry. Solution Shape is scored on structure and is NOT capped. Semantic analysis is independent of this build and covers every project that loaded — but a project whose restore did not complete has no resolved references, so treat its results as absent rather than clean. Worth checking on your side too: a build that needs undeclared host tooling, or that cannot run off its own platform, is the same wall a new contributor hits.
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.
dotnet: not applicable — `dotnet list package --vulnerable` could not read this solution's dependency graph — it reported an error for at least one project and returned no package data at all (typically a packages.config / non-PackageReference project, which the command cannot read; classic .NET Framework projects are packages.config by default). No packages could be enumerated, so there was nothing to scan for NuGet CVEs — excluded rather than scored, because an unreadable dependency graph is not a clean one; migrate the project(s) to PackageReference to enable this scan
trivy: not applicable — No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
trivy: not applicable — No JS/npm manifest or lockfile found outside build output (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
provenance: not applicable — No CI/build pipeline found (.github/.forgejo/.gitea workflows, .gitlab-ci.yml, azure-pipelines*.yml, .pipelines/, .vsts-ci/, Jenkinsfile, .circleci); there is no build to attest provenance for.
disclosure: not applicable — No vulnerability-disclosure policy file found (SECURITY.md/.markdown/.rst/.txt at root or under .github/.forgejo/.gitea/docs, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; network egress policy is a cluster-native control that may live at the platform/firewall layer, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; seccomp/AppArmor/SELinux confinement is a workload-level control, so there is nothing to assess here.
runtime-hardening: not applicable — No Kubernetes/orchestration workloads found in the repository manifests; runtime threat-detection and admission-control policy are cluster-level controls, so there is nothing to assess here.
0
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Run 01a00ac4-e343-7c62-a3b2-c5210fe39bca · every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Issues: 5 · Warnings: 56 · Recommendations: 19 · Info: 3 — Appendix A · all findings · full markdown report.
Generated by Watchdog — deterministic code-health analysis. 16-08-2026 @ 13:31 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.