Public report β .NET-Domain-Driven-Design-Template, published 19 Jun 2026.
Concrete security findings (CVE IDs, secret matches, dependency versions) are hidden in this version;
ask the repo owner for the full report.
62findings with an exact file:lineof 101 β the remainder are repo-wide signals (a dimension-level measurement, not a single line); open any file:line and verify
59/101dimensions across the health lenses4217 LoC Β· 21 projects β wide & deep
Executive summary
Read through the Template lens: this is a template / kata / sample / demo β code meant to be read or copied, not operated. The ship-it and operate-it dimensions (CI/CD, observability, ADRs, architecture docs, deployment security) are N/A, and the colour bands on what remains are relaxed to what an example needs. Code correctness stays near-strict; the score is absolute and comparable across repos.
evgenirusev/.NET-Domain-Driven-Design-Template is in good overall health (63%), but at least one category below sits in Fair-or-worse territory β most items are improvements, and the weakest category contains work to schedule, not shelve.
It is strongest in Event-Driven (100%) β its messaging keeps components properly decoupled. Architecture (84%) is solid too.
The area that most needs attention is Domain Modelling (49%) β the domain model leaks and drifts, so business rules are harder to trust and change. Maturity (69%) is the next concern β onboarding is slow β key decisions and the architecture aren't written down, so contributors have to reverse-engineer the intent.
Leadership focus, highest impact first: `AddStandardResilienceHandler()` (or Polly policies) to your⦠(Outbound HTTP resilience); Set RequireHttpsMetadata = true in prod (or pin MetadataAddress⦠(Web-Security Posture); Define repositories per aggregate root (Repository granularity).
For scale: Small (~4,217 production lines); rebuilding it from scratch would take roughly ~0.1 person-years (~1 engineer). Approximate, ±~30%.
It builds on a genuinely strong Event-Driven foundation (100%); the priorities above are the highest-leverage way to bring the rest up to that level.
A full-fidelity diff against the previous run's complete recorded findings β line-move tolerant: a finding that only shifted line counts as unchanged, only genuinely new titles/files surface here.
Rebuild cost & value ~ Modeled β β¬1,900ββ¬9,500
This codebase represents roughly ~0.1 person-years of build effort (about ~β¬5,700 to rebuild). Its weakest lens is Domain Modelling at 49% β the part of that asset most exposed by the findings below.
How we model this: boilerplate at a scaffolding rate + logic × domain High (×1.6) β service/app, CQRS, domain model, event-driven integration × a 0.9× quality factor, at β¬60β95/h; indicative, ±~30%. Indicative only β 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 5 Orphaned knowledge finding(s) in Knowledge Freshness β start with Enumeration.cs, InfrastructureConfiguration.cs, Product.cs.
Value concentrated against a weak lens Β· Medium Β· Value at risk
This is a Small asset (~0.1 person-years to rebuild), and its weakest lens is Domain Modelling at 49%. The operational and business risk on an asset this size concentrates there β that's where remediation buys the most protection.
β Direct remediation budget at Domain Modelling first β highest risk-reduction per euro on an asset this size.
Highest-leverage move Β· Medium Β· Leverage
Of everything flagged, the best return on effort is: Add `AddStandardResilienceHandler()` (or Polly policies) to your HttpClient registrations so a flaky dependency can't take the app down. The rest can wait behind it.
Evidence: priority ranking: top of 5 ranked by impact/effort
β Add `AddStandardResilienceHandler()` (or Polly policies) to your HttpClient registrations so a flaky dependency can't take the app down.
Improving trajectory Β· Info Β· Trajectory
The headline is improving steadily (+15.2 pts/run over 3 runs) β whatever you're doing is working; keep the gate.
Evidence: trajectory: +15.2 pts/run over 3 runs
Architecture β bounded-context dependency graph
Each box is a bounded context (its layer projects grouped, or a project count when large); arrows show dependencies between contexts. A shared kernel is where many arrows converge.
First, enhance outbound HTTP resilience by adding standard resilience handlers to HttpClient registrations to prevent dependency failures from taking the app down. Next, secure the web posture by requiring HTTPS metadata in production and ensuring secure headers and cookies are properly configured. Then, enforce repository granularity by defining repositories per aggregate root to protect invariants and reach child entities safely. After that, implement policy-based authorization to explicitly define and enforce access rules across the application. Finally, complete the migration to strongly-typed IDs to prevent transposed-argument bugs and ensure domain integrity.
Ranked by impact Γ· effort. "Helps" is the estimated gain on the 0β100 health score.
Do this
Helps
Effort
Dimension
Resolve the 5 Orphaned knowledge finding(s) in Knowledge Freshness β start with Enumeration.cs, InfrastructureConfiguration.cs, Product.cs.
Resolve the 3 redundant comment finding(s) in Comment Value β start with 20240622132132_InitialMigration.Designer.cs, ModelConstants.cs, Supplier.cs.
Add policy-based authorization β name the access rules (AddAuthorization(o => o.AddPolicy(β¦))) and apply them via [Authorize(Policy = β¦)] or RequireAuthorization.
Watchdog is a deep, periodic assessment β 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. 56 of 59 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 0.7 β 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: β Measured β a deterministic fact (LoC, complexity, coverage); ~ Modeled β an estimate from a stated model (cost, effort, value-at-risk), always a range with its assumptions, never a precise fact; β Advisory β 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): β Tool-verified means the property itself was measured across the surface; β Nothing flagged means the probes came back clean β a claim bounded by what a repository can show; β Not evidenced means a working control (a tested restore, an automated rollback) showed no positive evidence β absence of evidence is not evidence of a control, so it's excluded from the score rather than awarded a spurious 10; β Sampled Β· advisory marks an LLM verdict over a bounded sample β advisory, never a deterministic measurement.
What we checked β 59 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 β in one coherent pass. A surface report typically covers a handful.
How to trust any code-health report β three questions
Can you open the finding? Real findings cite a repo-relative file and line you can open at the cited line β never an absolute scratch path. Here, 62 of 101 do; the remainder are repo-wide signals β 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 β Roslyn, git, a scanner, or (for a handful of documentation/naming dimensions) an LLM labelled sampled Β· advisory β not a narrative.
Does re-running give the same result? Run it again on the same commit and the score β and this report, byte for byte β 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) β 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 β 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 β scanner not present in this environment β 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) β scanner not present in this environment β 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 β scanner not present in this environment β 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 β scanner not present in this environment β 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 β scanner not present in this environment β 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 β scanner not present in this environment β 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 β 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 β 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 β the honest edge of the measurement, not a failure of it.
D1 Cyclomatic Complexity: Cyclomatic complexity counts branches statically β 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 β 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 β one class/IIFE β earns a 3× threshold), but cohesion is approximated from top-level declarations, not true dependency structure.
D4 Code Duplication: Duplication is token-similarity (jscpd) β it finds copy-paste, not semantic duplication expressed differently. Committed machine-written code (EF migration scaffolds, *.Designer.cs, model snapshots) is EXCLUDED β its repetition is the tool's, not the team's β 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 β runtime coupling through DI, reflection, messaging or shared databases is invisible to a static reference graph.
D6 Cohesion (LCOM4): LCOM4 cohesion is syntactic β it infers connectivity from which methods touch which fields/methods by name, not from real runtime behaviour or intent.
D9 Test Distribution: The test-pyramid shape is inferred from project/folder naming and references, with a single test host bucketed per-file by its path tier and content signals β a suite that names tiers unconventionally and gives no per-file signal can still be mis-bucketed.
D10 Test Quality: Assertion density is structural β it cannot tell a meaningful behavioural assertion from a trivial one, only that an assertion is present.
D11 Test Reliability: Flakiness is inferred from history/markers β Watchdog runs the suite once (for coverage), not the repeated runs under varied conditions that reveal nondeterminism, so a flaky test never recorded as failing is invisible here.
D12 Dependency Hygiene: Dependency health reads manifests and lockfiles β 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 β a secret that does not match a known pattern, or one already rotated, will not be flagged (a clean scan is "nothing matched", not "no secrets exist").
D14 License Compliance: License compatibility is checked against declared package metadata and a policy β mislabelled or missing license metadata, and obligations that depend on how you distribute, are not resolved here.
D15 Churn × Complexity Hotspots: Churn hotspots come from git history β 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 β 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 β 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 β it is never the team's dead code to delete.
D18 Solution Shape: Build integrity reflects whether the solution compiled in this environment β 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 β 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 β it assesses clarity/consistency of the names it sees, not domain-correctness, and is advisory.
D22 Internal API Consistency: API-surface coherence is an LLM judgement over a sample of the public surface β consistency of intent across the whole API is approximated, not exhaustively verified.
D24 Comment Value: Comment value (WHY vs WHAT) is an LLM judgement over a bounded sample β 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 β a project that is broad by deliberate design reads the same as one that has sprawled.
D27 Navigability: Indirection/navigability is structural β it measures hops to follow a call, not whether that indirection buys real flexibility or just ceremony.
D28 Secrets (history): Secret-history scanning sweeps the git log for known patterns β 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) β 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 β 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 β 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 β 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 β 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.
AX9 CQS / query purity: Handlers are found by interface/name convention β a query handler using neither is not seen. Mutation is a resolved write/publish invocation (SaveChanges/repository/bus), so a write hidden behind a hand-rolled wrapper, reflection, or a string-keyed service locator resolves to a non-persistence type and isn't flagged; it detects that a query writes state, not whether the write is a legitimate read-side cache update. Clean means "no resolved write/publish in a query body", not a proof of CQS purity.
DM4 Rich vs anemic model: Behaviour is detected as state mutation inside a method body β a method that enforces an invariant by validating-and-throwing without mutating reads as a query, and mutation delegated through an interface the scan can't resolve isn't credited; entities with zero public properties still drop out of the population. It detects that state changes, not whether the rule is correct.
DM6 Domain β infrastructure boundary: Infrastructure reached through a hand-rolled wrapper, a domain-named facade, reflection, or a string-keyed service locator resolves to a non-infra type and isn't seen; the body scan is symbol resolution over syntax, not full dataflow. A clean result means "no resolved infra reference in a domain body", not a proof of purity.
M4 Documentation accuracy: Onboarding quality is an LLM read of the docs/setup present β it cannot run the onboarding or measure how long a real new joiner takes; the verdict is sampled and advisory.
The LLM boundary
LLM-set scores this run (5): D19, D21, D22, D24, M4 (model: Qwen/Qwen3.5-35B-A3B). For these, a model reads a bounded sample and sets the numeric score (documentation, ADR quality, naming, comment value, onboarding) β 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 β 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.
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.
0 method(s) exceeded the cognitive complexity threshold of 15.
β On the Gold path β maintain.
Detailed fixes: d2_recommendation.md.
Do you agree with this assessment?
D3 Β· God Classes10.0 / 10Exemplaryβ 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.
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.
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 β 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 β the population is all types, not a name convention.
Resolve the 3 Low cohesion finding(s) in Cohesion (LCOM4) β start with Enumeration.cs, Order.cs, Product.cs. β One of this dimension's main actionable groups (3 warning-level).
Enforce Cohesion (LCOM4) in CI to reach Verified (currently Documented). β Hardens enforcement from Documented toward Verified β provenance only; does not change the score.
Detailed fixes: d6_recommendation.md Β· top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D9 Β· Test Distribution10.0 / 10Exemplaryβ 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.
3 test methods: 3 unit, 0 integration, 0 BDD, 0 e2e.
Unit tests
Integration tests
BDD tests
E2E tests
β On the Gold path β maintain.
Detailed fixes: d9_recommendation.md Β· top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D10 Β· Test Quality10.0 / 10Exemplaryβ Tool-verified
What it measures: Whether the tests truly assert behaviour rather than just running the code.
Method: Per-test assertions, skips, and mock references analyzed via Roslyn; structured skip-reason tags (BUG:/ENV:) separate documented deferrals from debt. Deterministic.
0 skipped, 0 zero-assertion, no mocking-framework packages referenced (hand-written doubles or no mocking) across 3 tests.
β On the Gold path β maintain.
Detailed fixes: d10_recommendation.md.
Do you agree with this assessment?
D11 Β· Test Reliability10.0 / 10Exemplaryβ Tool-verified
What it measures: Whether the tests pass reliably, with no flakiness.
Method: Suite re-run N times within tiered wall-clock budgets (unit to e2e); tests failing non-deterministically across runs flagged; guarded tests retried when #if guards detected.
What it measures: Whether dependencies are current, secure, and not bloated.
Method: Manifest scan via dotnet list package across all projects; worst-signal-per-package deduction (saturating for vulnerabilities, capped-linear for deprecation/outdated) per KLoC. Exhaustive, deterministic.
Resolve the 2 Deprecated finding(s) in Dependency Hygiene. β One of this dimension's main actionable groups (2 warning-level).
Enforce Dependency Hygiene in CI to reach Verified (currently Documented). β Hardens enforcement from Documented toward Verified β provenance only; does not change the score.
Detailed fixes: d12_recommendation.md Β· top locations in Appendix A, every location in findings.md.
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: Whether the licenses of third-party packages are compatible with your policy.
Method: Third-party package licenses resolved from declared package metadata and checked against the configured policy (allow/deny/copyleft). Deterministic; clean = no incompatible license found at metadata depth.
What it measures: Files that change often and are also complex β the riskiest hotspots.
Method: Per production file churn times cyclomatic complexity over a rolling window, computed from git and Roslyn/JS/Razor analysis. Exhaustive, deterministic per commit date.
What it measures: Whether knowledge is concentrated in too few people (the "bus factor").
Method: Living knowledge per author via time-decayed commit attribution (6-month half-life, focus weighting) across largest source files. Deterministic, avoids blame's mechanical-refactor false positives.
4 source file(s) have their living knowledge concentrated in one author (β₯90% of recent, decayed contribution). The largest is Common/Common.Infrastructure/InfrastructureConfiguration.cs, held by evgeni.n.rusev@gmail.com.
Resolve the 4 Knowledge silo finding(s) in Bus Factor β start with Enumeration.cs, InfrastructureConfiguration.cs, Order.cs. β One of this dimension's main actionable groups (4 warning-level).
Resolve the 1 Off-boarding risk finding(s) in Bus Factor. β One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d16_recommendation.md Β· top locations in Appendix A, every location in findings.md.
What it measures: Acknowledged debt left in the code β 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.
The project documentation is critically deficient. The sole README file is truncated, cutting off the 'Core Principles' section mid-sentence, which severely impacts readability. Furthermore, there are no architecture or design documents, and XML documentation coverage across all 18 projects is effectively 0%, indicating a complete lack of inline code documentation. The README also lacks critical setup instructions, such as how to build or run tests.
Resolve the 20 Low XML-doc coverage finding(s) in Documentation Quality β start with Common.Application.csproj, Common.Domain.csproj, Common.Infrastructure.csproj. β One of this dimension's main actionable groups (20 warning-level).
Detailed fixes: d19_recommendation.md Β· top locations in Appendix A, every location in findings.md.
What it measures: Whether names β types, methods, variables β 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.
4 naming inconsistencies across 200 sampled symbols.
Inconsistent repository interface naming convention. Some repositories use a 'Domain' suffix in the interface name (e.g., IOrderDomainRepository), while others use a 'Query' suffix (e.g., IOrderQueryRepository). Additionally, there is a generic IQueryRepository<TEntity> and a concrete DataRepository, but the specific domain/query split is not applied consistently across all entities (e.g., Product has both Domain and Query interfaces, but the pattern is not uniform for all entities).
Inconsistent naming for constants/configuration classes. Some use the pattern '{Entity}ModelConstants' (e.g., OrderModelConstants, SupplierModelConstants), while others use a generic name like 'CommonModelConstants'.
Inconsistent naming for CQRS commands. Most commands are named with a specific action (Create, Update, Delete, Register, ChangePassword), but there is a generic 'OrderCommand' which is ambiguous compared to the specific 'CreateOrderCommand' and 'UpdateOrderCommand' also present.
Inconsistent naming for DTOs/Models. Some use the 'Model' suffix (ProductModel, OrderModel), while others use 'Response', 'Request', or 'ListItem'. This makes it difficult to distinguish between internal domain models, request DTOs, and response DTOs.
What to do
Resolve the 1 Inconsistent repository interface naming convention. Some repositoriesβ¦ finding(s) in Naming Consistency. β One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 Inconsistent naming for constants/configuration classes. Some use theβ¦ finding(s) in Naming Consistency. β One of this dimension's main actionable groups (1 recommendation-level).
Resolve the 1 Inconsistent naming for CQRS commands. Most commands are named with aβ¦ finding(s) in Naming Consistency. β One of this dimension's main actionable groups (1 recommendation-level).
Detailed fixes: d21_recommendation.md Β· top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D22 Β· Internal API Consistency / 10Exemplaryβ Sampled Β· advisory
What it measures: Whether the internal API surface is consistent and coherent.
Method: Judged by language model at low temperature over a sample of the public API surface (IsPackable or .Contracts types). Sampled, advisory; confidence discounted by model uncertainty.
No public API surface exposed; nothing to be inconsistent.
No exposed public API
β On the Gold path β maintain.
Detailed fixes: d22_recommendation.md Β· top locations in Appendix A, every location in findings.md.
Do you agree with this assessment?
D24 Β· Comment Value / 10Poorβ Sampled Β· advisory
What it measures: Whether comments are worth it β 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.
Resolve the 3 redundant comment finding(s) in Comment Value β start with 20240622132132_InitialMigration.Designer.cs, ModelConstants.cs, Supplier.cs. β One of this dimension's main actionable groups (3 recommendation-level).
Detailed fixes: d24_recommendation.md Β· top locations in Appendix A, every location in findings.md.
What it measures: How far you must trace to follow a call β low indirection and co-located slices read easier.
Method: Call indirection (interface hops, cross-namespace calls, slice-locality scaled) over a sampled set of method invocations, size-aware baseline. Sampled; confidence discounted by symbol-resolution gaps.
Coverage: Slice locality from the first namespace segments, SAMPLED (β€400 methods) β not exhaustive.
90 % of calls cross a namespace and 5 % go through an interface, but 100 % of collaborators are co-located β so a call's collaborators sit together and tracing stays easy. Baseline: small β navigation cost is tolerated.
What it measures: Whether any secrets were ever committed β 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 β likely security bugs in the code, any language.
Method: Polyglot static analysis via semgrep --config auto across the repo; severity rules (ERROR/WARNING/INFO) map to a 0-10 wide normalizer. Exhaustive, deterministic; degrades on parse failure.
Coverage: semgrep pattern rules over all files β exhaustive for the rule set, blind to classes of bug without a rule (clean = no rule matched).
What it measures: Whether any dependencies have known published vulnerabilities (CVEs), direct or transitive.
Method: NuGet CVE scan via dotnet list package --vulnerable including transitive; severity tally (Critical/High/Medium/Low) to 0-10 tight normalizer. Exhaustive, deterministic; degrades when absent.
What it measures: Whether anyone still has living knowledge of each file, or it has been orphaned β 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.
5 of 6 significant source file(s) are orphaned β their living knowledge has decayed to nothing, so no one currently understands them. The largest is Common/Common.Infrastructure/InfrastructureConfiguration.cs.
Resolve the 5 Orphaned knowledge finding(s) in Knowledge Freshness β start with Enumeration.cs, InfrastructureConfiguration.cs, Product.cs. β One of this dimension's main actionable groups (5 warning-level).
Detailed fixes: d34_recommendation.md Β· top locations in Appendix A, every location in findings.md.
What it measures: Whether files that change together actually belong together β 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 β tests and generated dropped): Degree-of-Coupling = shared ÷ min individual revisions, reported above noise floors (each file β₯10 revisions, β₯5 shared commits, β₯50% strength); sweeping commits excluded. Deterministic over fixed history.
Coverage: Population: PRODUCTION source files only β test and generated files are dropped before pairing, so a class co-changing with its own test (trivially ~100%) can't drown the real productionβproduction coupling. Pairs ranked by Degree-of-Coupling; coupling through a build step, config, or non-source file isn't seen.
Other Β· Architecture β Whether any singleton service captures a scoped/transient dependency β a silent lifetime/threading bug.
Method: Roslyn scan: DI registrations parsed from AddSingleton/Scoped/Transient; each singleton checked for captured shorter-lifetime dependencies. Exhaustive, deterministic.
Other Β· Architecture β How the codebase splits by code ROLE β 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 β 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.
Other Β· Architecture β 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 Β· Architecture β 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 Β· Architecture β Whether interfaces stay focused rather than fat β the Interface-Segregation principle (SOLID 'I').
Method: Roslyn scan: public interface member counts; fat-interface threshold (over 15 members) flagged per type. Deterministic, type-level.
Do you agree with this assessment?
AX8 Β· Test isolation10.0 / 10Exemplaryβ Tool-verified
Other Β· Architecture β Whether production projects stay free of references to test projects β tests may depend on production, never the reverse.
Method: Csproj graph: each production project checked for references to test projects (identified by test-framework presence, not name). Zero violations is clean. Deterministic.
Other Β· Architecture β Whether read (query) handlers stay side-effect-free β a query that writes persistent state or raises events breaks CQS and makes reads unsafe to retry, cache, or route to a read replica.
Method: Roslyn scan: CQRS handlers classified query-vs-command by interface (IQueryHandler/ICommandHandler/IRequestHandler<TQuery,TResult>) and name convention (*Query/Get*/Find* vs *Command); each query handler's body checked for persistent-state writes (SaveChanges/repository Add-Update) or event publishes by resolved invocation. Deterministic, type-level, exhaustive over the detected handlers.
Coverage: Population: CQRS handlers identified by IQueryHandler/ICommandHandler/IRequestHandler interface + *Query/Get*/Find*/*Command NAME convention; query purity then checked exhaustively within that set β a query handler using neither convention is invisible, and mutation is a resolved persistence/publish CALL, not full dataflow.
Other Β· Security β Whether access is authorized by default β [Authorize]/policies or imperative guard methods (throw-on-violation) called from handlers.
Method: Roslyn scan: [Authorize] usage and authorization policies, plus imperative throw-on-violation guard methods detected via syntax. Deterministic.
Authorization IS enforced here (via [Authorize]/guards) β this is NOT a claim that endpoints are unprotected. What's missing is NAMED policies (AddAuthorization/AddPolicy, RequireRole/RequireClaim, RequireAuthorization): the access rules are implicit rather than named and testable. Recommendation, not a defect β name the rules so they're reviewable.
What to do
Add policy-based authorization β name the access rules (AddAuthorization(o => o.AddPolicy(β¦))) and apply them via [Authorize(Policy = β¦)] or RequireAuthorization.
Other Β· Domain Modelling β Whether aggregates reference each other by identity (id) rather than by direct object reference β the core DDD consistency-boundary rule.
Method: Roslyn (DDD-gated): aggregate roots identified by convention; each aggregate field checked for direct references to other aggregates versus id-only. Deterministic, DDD-native.
Coverage: Population: aggregate roots identified by AggregateRoot/IAggregateRoot base/interface NAME convention; reference-by-identity then checked exhaustively within that set β a root not using those names is invisible.
`Product` references the aggregate root `Supplier` directly (via `Suppliers`) β hold its `SupplierId` instead. β Product.cs:3
`Supplier` references the aggregate root `Product` directly (via `Products`) β hold its `ProductId` instead. β Supplier.cs:37
What to do
Reference other aggregates by their strongly-typed id, never by object reference, so each aggregate stays an independent consistency boundary.
Other Β· Domain Modelling β How much of the domain uses strongly-typed ids vs raw Guid/string/int β adoption curve, not all-or-nothing.
Method: Roslyn (DDD-gated): strongly-typed id adoption on domain entities/events; raw Guid/int/string ids counted versus wrapped types. Deterministic, adoption percentage.
Coverage: Population: id-like members by *Id/*Key NAME suffix; strongly-typed-ID shape then checked semantically β non-suffixed identifiers are not seen.
`Order.CustomerId` is a raw `Guid` β give it a strongly-typed id (`readonly record struct CustomerId { Guid Value }`). β Order.cs:17
`OrderItem.OrderId` is a raw `Guid` β give it a strongly-typed id (`readonly record struct OrderId { Guid Value }`). β OrderItem.cs:12
`OrderItem.ProductId` is a raw `Guid` β give it a strongly-typed id (`readonly record struct ProductId { Guid Value }`). β OrderItem.cs:13
What to do
Adopt strongly-typed ids across the domain β finish the migration or document the boundary; primitive ids invite transposed-argument bugs.
Do you agree with this assessment?
DM4 Β· Rich vs anemic model8.6 / 10Exemplaryβ Tool-verified
Other Β· Domain Modelling β Whether aggregates/entities carry the behaviour that protects their invariants, rather than being data bags driven by external services.
Method: Roslyn (DDD-gated): entity method BODIES classified mutator-vs-query β only methods that mutate the entity's own declared state count as invariant-protecting behaviour, so a getter/passthrough doesn't rescue an anemic class. Deterministic, exhaustive over domain-layer entities.
Coverage: Population: entities by name/base convention; rich-vs-anemic judged by classifying each method body mutator-vs-query β logic-bearing domain types outside the convention are invisible.
`Supplier` is an aggregate/entity with 5 data propert(ies) but no state-changing behaviour (only data and queries) β the business logic lives in a service. β Supplier.cs:1
What to do
Move business rules onto the aggregates/entities they govern so invariants are enforced at the source, not in anemic services.
Other Β· Domain Modelling β Whether entities protect their state (private/init-only setters) instead of exposing public setters that bypass invariants. Softened when a rehydration framework (Marten/EF) is present.
Method: Roslyn (DDD-gated): public setters on entities detected; score softened when Marten/EF rehydration frameworks present. Deterministic, framework-aware.
Coverage: Population: entities by convention; encapsulation (setter shape) checked exhaustively within the set.
Other Β· Domain Modelling β Whether the domain layer stays free of infrastructure dependencies (EF/Marten/HTTP/ASP.NET) β the clean-architecture dependency rule.
Method: Roslyn (DDD-gated): domain-layer types scanned for infrastructure usage in member SIGNATURES and inside method/accessor BODIES β resolved calls and object-creations into EF/Marten/HTTP/Mongo/Redis/message-bus types (not just a namespace allowlist). Deterministic, symbol-resolved, exhaustive over domain-layer bodies, DDD-native.
Coverage: Domain layer identified by NAMESPACE heuristic; infrastructure then resolved by symbol in member SIGNATURES and method/accessor BODIES β rename the layer and the check evaporates.
Coverage: Population: repositories + aggregate roots by NAME convention; per-root repository rule checked within the set.
`OrderRepository` is a repository over `Order`, which is an entity but not an aggregate root. Repositories should be per aggregate ROOT β loading/saving a child entity independently lets callers bypass the root's invariants. Access `Order` through its owning aggregate instead. (×2) β OrderRepository.cs:4, OrderRepository.cs:4
`IOrderQueryRepository` is a repository over `Order`, which is an entity but not an aggregate root. Repositories should be per aggregate ROOT β loading/saving a child entity independently lets callers bypass the root's invariants. Access `Order` through its owning aggregate instead. β IOrderQueryRepository.cs:1
`ProductRepository` is a repository over `Product`, which is an entity but not an aggregate root. Repositories should be per aggregate ROOT β loading/saving a child entity independently lets callers bypass the root's invariants. Access `Product` through its owning aggregate instead. (×2) β ProductRepository.cs:4, ProductRepository.cs:4
`StatisticsRepository` is a repository over `TotalStatistics`, which is an entity but not an aggregate root. Repositories should be per aggregate ROOT β loading/saving a child entity independently lets callers bypass the root's invariants. Access `TotalStatistics` through its owning aggregate instead. (×2) β StatisticsRepository.cs:4, StatisticsRepository.cs:4
`IStatisticsQueryRepository` is a repository over `TotalStatistics`, which is an entity but not an aggregate root. Repositories should be per aggregate ROOT β loading/saving a child entity independently lets callers bypass the root's invariants. Access `TotalStatistics` through its owning aggregate instead. β IStatisticsQueryRepository.cs:1
What to do
Define repositories per aggregate root; reach child entities through their root so invariants can't be bypassed.
Other Β· Domain Modelling β Whether clusters of primitives that travel together (a missing value object) are extracted β a low-weight suggestion, LLM-confirmed when configured.
Method: Roslyn (DDD-gated): primitive parameter clusters recurring three or more times across signatures extracted, then confirmed by language model when configured. Advisory, low-weight.
Other Β· Event-Driven β Whether event handlers stay asynchronous (no blocking remote HTTP/gRPC calls awaited inside a handler).
Method: Roslyn semantic scan (event-driven gated): event-handler bodies scanned for HTTP/gRPC invocations by resolved symbol type, not substring. Deterministic, semantic-resolved.
Other Β· Event-Driven β Whether commands have a single handler (one owner of the decision) and fan-out is modelled with events.
Method: Roslyn scan (event-driven gated): command-shaped messages identified by convention; handler count per command checked for the exactly-one rule. Deterministic, hard fact.
Other Β· Event-Driven β Whether events are named in the past tense (a clarity nudge β low weight).
Method: Roslyn scan (event-driven gated): domain and integration events checked for past-tense naming (-ed/-en suffix or irregular set). Naming nudge, low-weight advisory.
`OrderAddedEvent` reads as an instruction, not a fact that happened. Events describe something that already occurred β name them in the past tense (e.g. `OrderPlaced`, `PaymentCaptured`) so the ubiquitous language stays clear. β OrderAddedEvent.cs:1
`ProductAddedEvent` reads as an instruction, not a fact that happened. Events describe something that already occurred β name them in the past tense (e.g. `OrderPlaced`, `PaymentCaptured`) so the ubiquitous language stays clear. β ProductAddedEvent.cs:1
What to do
Name events in the past tense β they record facts that already happened.
Other Β· Code Health β 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 Β· Code Health β 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.
Maturity Β· Maturity β 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 β how to run the test suite.
Add a README to the 21 of 21 project(s) that lack one β worth up to 2 pts.
Maturity Β· Maturity β Whether the repo is organised deliberately β 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 β production and tooling code are mixed at the root.
Only 5/21 projects share a common root namespace β the code's module identity is inconsistent.
What to do
Group production code under src/ (or split deliberately, e.g. backend/ + frontend/) so production and tooling code aren't mixed at the root.
Adopt a consistent root-namespace convention (a shared prefix, e.g. Acme.*); short project-file/directory names are fine as long as the RootNamespace is uniform.
Maturity Β· Maturity β 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.
Readiness Β· Readiness β Whether outbound HTTP calls are wrapped in resilience (retry/timeout/circuit-breaker) so a failing dependency doesn't cascade.
Method: Roslyn scan: Polly resilience markers (Retry, CircuitBreaker, Timeout) on outbound HTTP invocations. Computed per type, deterministic.
The app makes outbound HTTP calls but no resilience handler was detected (Polly / AddStandardResilienceHandler / circuit-breaker). A slow or failing dependency will cascade β add timeouts, retries with back-off, and a circuit breaker.
What to do
Add `AddStandardResilienceHandler()` (or Polly policies) to your HttpClient registrations so a flaky dependency can't take the app down.
Other Β· Security β Transport security, security headers, secure cookies, input validation, middleware order and crypto hygiene (presence, not runtime).
`RequireHttpsMetadata = false` allows the OIDC discovery doc to be fetched over plain HTTP. Safe for loopback-only fetches (Aspire / on-host); risky for any other path. β InfrastructureConfiguration.cs:38
No Content-Security-Policy / X-Frame-Options / X-Content-Type-Options configuration found β defense in depth, even when a reverse proxy could set them. (β2.0 on this card.)
No CookieSecurePolicy/HttpOnly/SameSite configuration found. (β1.5 on this card; skip if the app sets no cookies.)
What to do
Set RequireHttpsMetadata = true in prod (or pin MetadataAddress to a localhost URL the API can hit directly).
Add security response headers (Content-Security-Policy, X-Frame-Options, X-Content-Type-Options) β defense in depth, even when a reverse proxy could set them.
Set secure cookie flags β CookieSecurePolicy.Always, HttpOnly, and SameSite (Strict/Lax) on auth/session cookies. Skip only if the app sets no cookies.
Other Β· Code Health β 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.
Blocking on a Task with `.Wait()`/`.GetAwaiter().GetResult()` can deadlock (and wastes a thread). Make the caller `async` and `await` instead. β IdentityDbInitializer.cs:26
Other Β· Code Health β Whether async methods accept a CancellationToken so work can be cancelled (adoption curve).
Method: Roslyn scan: every async method (excluding framework-fixed overrides/Blazor handlers) checked for CancellationToken parameter presence. Deterministic, adoption percentage.
Only 24/46 async methods accept a CancellationToken, so requests can't be cancelled cleanly under load or on client disconnect. In Blazor Server circuits and other short-write hosts, omitting it can be an accepted convention β judge against your hosting model.
No CancellationToken parameter β work can't be cancelled cleanly on disconnect/shutdown. (×22) β EventDispatcher.cs:23, ImageService.cs:8, ImageService.cs:18, β¦
What to do
Thread a CancellationToken through async methods so work stops promptly on cancellation.
Other Β· Code Health β Whether exceptions are handled rather than silently swallowed or rethrown with lost stack traces.
Method: Roslyn syntax scan: every catch clause counted; empty catches and bare rethrows flagged. Population is all catch clauses, not estimated. Deterministic, hard fact.
Other Β· Code Health β 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.
Other Β· Code Health β Whether nullable reference types are enabled and not undermined by heavy `!` suppression.
Method: Roslyn compiler-options scan: NullableContextOptions per project; null-forgiving (!) suppression density per 1k syntax nodes. Deterministic, adoption plus suppression penalty.
~1.3 `!` suppressions per 1k syntax nodes β each one tells the compiler to trust you about null, suppressing the very safety NRTs provide.
What to do
Enable <Nullable>enable</Nullable> across all projects and resolve warnings rather than suppressing with `!`.
Do you agree with this assessment?
Reference β 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 β¦") and is never the strongest area however high its average.
Not included β 42 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 β No web markup found β accessibility is not applicable to this repository.
AC2 Forms & labels β No web markup found β accessibility is not applicable to this repository.
AC3 Page structure β No web markup found β accessibility is not applicable to this repository.
AC4 Keyboard semantics β No web markup found β accessibility is not applicable to this repository.
AC5 ARIA correctness β No web markup found β accessibility is not applicable to this repository.
AC6 Visual & motion safety β No web markup found β accessibility is not applicable to this repository.
AC7 A11y enforcement β No web markup found β accessibility is not applicable to this repository.
AX2 Stateful singletons β no singleton implementations detected
AX4 Dependency direction β not applicable to a CQRS architecture (the inward-dependency rule is for layered/clean styles)
AX7 Slice cohesion β not applicable β not a vertical-slice architecture
C1 Data Protection β This is a dotnet-new template β at-rest encryption and key-vaulting are deferred to the application you build from it. Add ASP.NET Data Protection / column encryption + a key vault for your real data store when you productionise.
C3 Audit Trail β Repo shows no audit-logging mechanism (IAuditable, an immutable audit log, an EF SaveChanges interceptor) for sensitive changes β absence of evidence is not evidence of a working control. Record an audit trail in code (or document where it lives) so this dimension can be scored.
C4 Data Retention β Repo shows no data-retention / TTL / cleanup mechanism for personal data β absence of evidence is not evidence of a working control. Define retention periods and a purge/cleanup job (or TTL) in code, or document where retention is enforced, so this dimension can be scored.
C5 Data-Subject Rights β Repo shows no corroborated data-subject-rights mechanism (erasure / export-portability / consent) tied to a subject id or GDPR vocabulary β absence of evidence is not evidence of a working control. Implement erasure, data export/portability and consent tracking over the subject's records.
D20 ADR Quality β N/A β this repo declares itself a template / kata / sample / demo; a formal ADR log is deferred to a real application built from it.
D23 Boundary Type-Coupling β Bounded contexts not declared
D25 ADR Conformance β no ADRs to check
D31 IaC & Container Security β Not applicable
D32 Data Compliance (PII/GDPR) β Not applicable
D33 JS/npm Dependency Vulnerabilities β Not applicable
D36 Supply-chain Provenance & Signing β Not applicable
D37 Vulnerability-disclosure Policy β Not applicable
D38 OSV Dependency Vulnerabilities β Not applicable
D7 Architectural Integrity β No checkable ADRs to assess
D8 Code Coverage β Coverage not measured
DM3 Integration-event coupling β no integration events detected β coupling check not applicable
ED4 Outbox / dual-write β no persistence writes or publishes observed in handlers β atomicity not assessable
ED5 Idempotency β no mutating command handlers or message consumers detected β idempotency check not applicable
ES1 Event Sourcing β not run β 0/3 markers found
M2 Architecture documentation β This repo declares itself a template / kata / sample / demo β formal architecture documentation (ADRs, C4 diagrams) is deferred to a real application built from it, so its absence is not a defect here.
P12 CI test-gate honesty β no data
P2 Observability β This repo declares itself a template / kata / sample / demo β code meant to be read or copied, not operated. Structured logging, tracing/metrics and health checks are deferred to the application you build from it, so their absence is not a defect here. The dimension reactivates once the repo becomes a real app.
P3 Security & performance tooling β This repo declares itself a template / kata / sample / demo β code meant to be read or copied, not operated. SAST, secret/dependency scanning and performance benchmarks are deferred to the application you build from it, so their absence is not a defect here. The dimension reactivates once the repo becomes a real app.
P4 Deployment & Rollback β not evidenced β no deploy/rollback/approval signal in the repo; absence of evidence is not evidence of a manual release
P5 DR & Backup β not evidenced β repo shows no backup/RTO/RPO controls; absence of evidence is not evidence of a working control
P6 Release Hygiene β not evidenced β no changelog, version stamp or semver release tag in the repo
P9 Domain vs controller coverage β no coverage report found on disk β run tests with `--collect:"XPlat Code Coverage"` (or in CI) to enable this cross-layer check
PF1 Benchmark discipline β Performance is assessed only for perf-relevant repos β 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 β Performance is assessed only for perf-relevant repos β 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 β Performance is assessed only for perf-relevant repos β 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.
X6 Hand-rolled structured-format parsing β no data
X7 Silent fallback defaults β no data
Appendix A β 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.
Dead code: ImageService Common/Common.Infrastructure/Services/ImageService.cs:4β NamedType ImageService β no references found in solution.
Dead code: OrderFactory OrderManagement/OrderManagement.Domain/Factories/OrderFactory.cs:1β NamedType OrderFactory β no references found in solution.
Dead code: OrderRepository OrderManagement/OrderManagement.Infrastructure/Repositories/OrderRepository.cs:4β NamedType OrderRepository β no references found in solution.
Dead code: ProductFactory ProductCatalog/ProductCatalog.Domain/Factories/ProductFactory.cs:1β NamedType ProductFactory β no references found in solution.
Dead code: ProductRepository ProductCatalog/ProductCatalog.Infrastructure/Repositories/ProductRepository.cs:4β NamedType ProductRepository β no references found in solution.
Dead code: StatisticsRepository Statistics/Statistics.Infrastructure/Repositories/StatisticsRepository.cs:4β NamedType StatisticsRepository β no references found in solution.
Orphaned knowledge Common/Common.Infrastructure/InfrastructureConfiguration.csβ No living knowledge remains for this file β its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge Common/Common.Domain/Models/ValueObject.csβ No living knowledge remains for this file β its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge Common/Common.Domain/Specification.csβ No living knowledge remains for this file β its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge Common/Common.Domain/Models/Enumeration.csβ No living knowledge remains for this file β its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Orphaned knowledge ProductCatalog/ProductCatalog.Domain/Models/Products/Product.csβ No living knowledge remains for this file β its last meaningful change has decayed away; if it breaks, no one currently understands it. Schedule a read-through / add characterisation tests before it bites.
Knowledge silo Common/Common.Infrastructure/InfrastructureConfiguration.csβ 100 % of this file's living knowledge is held by evgeni.n.rusev@gmail.com β if they are unavailable, no one else has recently worked it.
Knowledge silo Common/Common.Domain/Models/Enumeration.csβ 100 % of this file's living knowledge is held by evgeni.n.rusev@gmail.com β if they are unavailable, no one else has recently worked it.
Knowledge silo ProductCatalog/ProductCatalog.Domain/Models/Products/Product.csβ 100 % of this file's living knowledge is held by evgeni.n.rusev@gmail.com β if they are unavailable, no one else has recently worked it.
Knowledge silo OrderManagement/OrderManagement.Domain/Models/Orders/Order.csβ 100 % of this file's living knowledge is held by evgeni.n.rusev@gmail.com β if they are unavailable, no one else has recently worked it.
Low cohesion: Product (LCOM4 5) ProductCatalog/ProductCatalog.Domain/Models/Products/Product.cs:1β Product's methods form 5 groups that share no state and don't call each other β a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: Enumeration (LCOM4 4) Common/Common.Domain/Models/Enumeration.cs:4β Enumeration's methods form 4 groups that share no state and don't call each other β a sign it may have several responsibilities. Review whether it splits into focused classes.
Low cohesion: Order (LCOM4 4) OrderManagement/OrderManagement.Domain/Models/Orders/Order.cs:1β Order's methods form 4 groups that share no state and don't call each other β a sign it may have several responsibilities. Review whether it splits into focused classes.
Off the main sequence: ProductCatalog.Domain β ProductCatalog.Domain: abstractness 0.11, instability 0.17, distance 0.72 β zone of pain β concrete and heavily depended-on, so it's rigid to change.
D8 Β· Code CoverageΒ· Coverage not measured Β· Γ1
Coverage not measured β The test suite couldn't be built/run in-image and no coverage report is committed, so line coverage was not measured β and it is EXCLUDED from the score rather than scored on a LoC-ratio proxy. Commit the Cobertura/OpenCover/lcov report your CI already produces (anywhere in the repo), or make the suite runnable in-image, and real coverage will be measured.
redundant comment Identity/Identity.Infrastructure/Migrations/20240622132132_InitialMigration.Designer.cs:1β "<auto-generated />" β Remove. This is a standard header that adds no value and clutters the file.
redundant comment OrderManagement/OrderManagement.Domain/Models/Orders/ModelConstants.cs:17β "Assuming a maximum of 10 digits for the price amount" β Remove or move to a code attribute/annotation if the limit is a business rule, otherwise it's just restating the type constraint.
redundant comment ProductCatalog/ProductCatalog.Domain/Models/Suppliers/Supplier.cs:51β "Add your email validation logic here" β Remove. This is a placeholder comment that should be deleted when the code is implemented.
Off-boarding risk: evgeni.n.rusev@gmail.com β If evgeni.n.rusev@gmail.com becomes unavailable, 4 significant file(s) lose their only recent owner β the largest single-person knowledge concentration (weighted toward the domain core). Pair, review, or document these before any departure.
D21 Β· Naming ConsistencyΒ· Inconsistent repository interface naming convention. Some repositories use a 'Domain' suffix in the interface name (e.g., IOrderDomainRepository), while others use a 'Query' suffix (e.g., IOrderQueryRepository). Additionally, there is a generic IQueryRepository<TEntity> and a concrete DataRepository, but the specific domain/query split is not applied consistently across all entities (e.g., Product has both Domain and Query interfaces, but the pattern is not uniform for all entities). Β· Γ1
Inconsistent repository interface naming convention. Some repositories use a 'Domain' suffix in the interface name (e.g., IOrderDomainRepository), while others use a 'Query' suffix (e.g., IOrderQueryRepository). Additionally, there is a generic IQueryRepository<TEntity> and a concrete DataRepository, but the specific domain/query split is not applied consistently across all entities (e.g., Product has both Domain and Query interfaces, but the pattern is not uniform for all entities). β Adopt a consistent naming convention for repository interfaces, such as I{Entity}Repository for all, or strictly separate I{Entity}QueryRepository and I{Entity}CommandRepository if using CQRS. (symbols: IOrderDomainRepository, IOrderQueryRepository, IProductDomainRepository, IProductQueryRepository, IFactory<TEntity>, IQueryRepository<TEntity>, DataRepository<TDbContext, TEntity>)
D21 Β· Naming ConsistencyΒ· Inconsistent naming for constants/configuration classes. Some use the pattern '{Entity}ModelConstants' (e.g., OrderModelConstants, SupplierModelConstants), while others use a generic name like 'CommonModelConstants'. Β· Γ1
Inconsistent naming for constants/configuration classes. Some use the pattern '{Entity}ModelConstants' (e.g., OrderModelConstants, SupplierModelConstants), while others use a generic name like 'CommonModelConstants'. β Rename 'CommonModelConstants' to a more specific name or align all constant classes with the '{Entity}ModelConstants' pattern if they represent specific entity configurations. (symbols: OrderModelConstants.OrderItem, SupplierModelConstants.Address, CommonModelConstants.Common)
D21 Β· Naming ConsistencyΒ· Inconsistent naming for CQRS commands. Most commands are named with a specific action (Create, Update, Delete, Register, ChangePassword), but there is a generic 'OrderCommand' which is ambiguous compared to the specific 'CreateOrderCommand' and 'UpdateOrderCommand' also present. Β· Γ1
Inconsistent naming for CQRS commands. Most commands are named with a specific action (Create, Update, Delete, Register, ChangePassword), but there is a generic 'OrderCommand' which is ambiguous compared to the specific 'CreateOrderCommand' and 'UpdateOrderCommand' also present. β Rename 'OrderCommand' to a more specific action (e.g., 'GetOrderCommand' or 'ProcessOrderCommand') or remove if redundant. (symbols: CreateProductCommand, UpdateProductCommand, CreateOrderCommand, UpdateOrderCommand, DeleteProductCommand, RegisterUserCommand, ChangePasswordCommand, OrderCommand)
D21 Β· Naming ConsistencyΒ· Inconsistent naming for DTOs/Models. Some use the 'Model' suffix (ProductModel, OrderModel), while others use 'Response', 'Request', or 'ListItem'. This makes it difficult to distinguish between internal domain models, request DTOs, and response DTOs. Β· Γ1
Inconsistent naming for DTOs/Models. Some use the 'Model' suffix (ProductModel, OrderModel), while others use 'Response', 'Request', or 'ListItem'. This makes it difficult to distinguish between internal domain models, request DTOs, and response DTOs. β Standardize DTO naming: use 'Model' for internal domain representations, 'Request' for inputs, and 'Response' for outputs, or consistently use 'Dto' suffix across all. (symbols: ProductModel, OrderModel, SupplierModel, OrderListItem, OrderResponse, ProductResponse, UserRequestModel, ImageRequestModel, OrderDetailsQuery)
D23 Β· Boundary Type-CouplingΒ· Bounded contexts not declared Β· Γ1
Bounded contexts not declared β The codebase contains 21 projects, indicating a multi-module architecture where implicit boundaries should be explicitly defined to manage coupling. Declare architecture.contexts (β₯2) in config to assess cross-boundary type coupling.
no ADRs to check β No ADRs found, so conformance can't be assessed.
D31 Β· IaC & Container SecurityΒ· Not applicable Β· Γ1
Not applicable β No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
D32 Β· Data Compliance (PII/GDPR)Β· Not applicable Β· Γ1
Not applicable β No PII/GDPR-handling patterns detected (p/gdpr ruleset) β no data-compliance surface to assess.
D33 Β· JS/npm Dependency VulnerabilitiesΒ· Not applicable Β· Γ1
Not applicable β 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 Β· Supply-chain Provenance & SigningΒ· Not applicable Β· Γ1
Not applicable β The CI pipeline builds and tests but publishes no released artifact β no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a NuGet package, a container image, a GitHub release).
D37 Β· Vulnerability-disclosure PolicyΒ· Not applicable Β· Γ1
Not applicable β 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 Β· OSV Dependency VulnerabilitiesΒ· Not applicable Β· Γ1
Not applicable β No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
D7 Β· Architectural IntegrityΒ· No checkable ADRs to assess Β· Γ1
No checkable ADRs to assess β No architecture decision records were found and the project graph is acyclic, so architectural integrity could not be assessed. Add ADRs (with `enforcement: analyzer|test`) to make the architecture's rules checkable.
Every external tool invocation behind a deep-scan dimension β 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 β 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 β kept out of this table so the rendered report stays byte-identical across runs of the same commit.
trivy: not applicable β No Infrastructure-as-Code or container manifests found (Dockerfile, Terraform, Kubernetes/Helm, CloudFormation); nothing to scan.
trivy: not applicable β No JS/npm manifest or lockfile found outside bin/obj (package.json, package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); no JS dependencies to scan.
provenance: not applicable β The CI pipeline builds and tests but publishes no released artifact β no package publish, container push, GitHub release or deployment step. Supply-chain provenance, signing and SBOM attest RELEASED artifacts, so there is nothing to attest here. Add them to the release pipeline when this repo starts shipping artifacts (a NuGet package, a container image, a GitHub release).
disclosure: not applicable β No vulnerability-disclosure policy file found (SECURITY.md, .github/SECURITY.md, docs/SECURITY.md, .well-known/security.txt). A coordinated-disclosure policy may live off-repo, so this is not evidenced rather than failed.
osv-scanner: not applicable β No JS/npm lockfile found outside bin/obj (package-lock.json, yarn.lock, pnpm-lock.yaml, bun.lockb); nothing for OSV to scan.
0
β
Run 019ee1ee-ebcb-714d-b694-dfa4bb16e4a1 Β· every finding is also locatable in findings.md, and the complete scoring record (with exit codes + durations) in sidecar.json.
Appendix C β Personal-data map
Every field, property and record parameter whose name is conventional personal data β 12 field(s) across 3 categories, each with an exact repo-relative file:line. This is the data inventory a compliance review starts from β right-to-erasure, retention, minimisation. Detected by name with a deliberately specific classifier (the same one the GDPR dimensions use, so CardDefinition or FileName don't trip); informational β it feeds no score.
Warnings: 42 Β· Recommendations: 17 Β· Info: 42 β Appendix A Β· all findings Β· full markdown report.
Generated by Watchdog β deterministic code-health analysis. 19-06-2026 @ 22:09 UTC.
Downloadable artifacts
Machine-readable and reproducible from this commit + frozen rubric β drop them straight into a contract appendix, a CRA dossier, or a downstream SCA / VEX tool.