4.0 KiB
4.0 KiB
QA-001 job-analysis and important-term quality
Updated: 2026-08-09
Status: IMPLEMENTED — NOT VERIFIED. Deterministic fixtures, backend/frontend regressions and production build pass. Browser and production presentation checks remain.
Revalidated execution path
- URL imports already convert structured job-posting HTML to text and run lightweight Norwegian/English language detection plus
SkillTagger. Manual descriptions and notes can still contain HTML/noise. - The visible problematic terms originate in
JobCvMatchService: curated skills are combined with frequency-ranked single tokens from description, translated description and notes. Its stop list was English-only and did not clean raw HTML at this boundary. - The separate application-analysis endpoint exposes only curated tags in its
Keywordsfield, and the current Analysis UI does not render that field. No AI prompt produces the deterministic match terms. - Match output is recomputed on every request; there is no stored analysis/result row or version to migrate. Missing-term learning items are derived through
SyncLearningRecommendationsAsync, which preserves user-completed/dismissed decisions and auto-completes only obsolete pending generated items.
Implemented contract
- The shared matcher removes script/style/navigation/header/footer blocks, remaining tags and decoded source chrome before analysis while preserving line boundaries.
- English and Norwegian function words, generic recruitment filler and common consent/navigation text are suppressed by category, not only by the reported examples.
- Stop words split bounded phrase runs. Useful two-to-four-word responsibility/domain phrases are ranked ahead of remaining single terms; tokens already represented by a phrase are not repeated as isolated advice.
- Curated, canonical tags now preserve C++, ASP.NET Core, Entity Framework Core, Go/Golang context, Next.js, Terraform, Azure DevOps, Kafka, Redis and Linux. Existing C#, .NET, Node.js and CI/CD punctuation remains intact.
- The UI says “important terms” rather than implying opaque SEO-style keywords, with equivalent Norwegian copy.
- Deterministic processing remains local and free; no model or external provider was added.
Verification
- Seven required fixtures pass: Norwegian, English, mixed, short, noisy HTML, technology-heavy and repeated recruitment filler.
- Final focused matcher: 15/15. Wider affected backend set: 54/54.
- Full backend: 601/601.
- Focused match/analysis UI: 13/13; final label test 3/3.
- Full frontend: 48/48 suites and 172/172 tests.
- Production frontend build/TypeScript and
git diff --check: pass.
Version and regeneration behavior
There are no historical analysis blobs to silently rewrite. The next GET recomputes from current job/CV text. When the missing-term set changes, existing sync logic creates new generated learning items, auto-completes obsolete pending generated items, and leaves explicit user decisions intact. No schema or data migration is required.
Remaining gates
- The browser session had already been finalized after UX-002; QA-001 label/chip presentation, empty/error/long Norwegian content and 375/768/1440 Light/Dark browser checks were not run in this package.
- Synthetic production comparison and rollout monitoring remain unavailable without deployment access.
- The curated vocabulary is intentionally bounded. New technologies should be added with representative false-positive tests rather than learned from private job data.
Evidence
- Evidence index:
docs/audits/evidence/qa-001/README.md - Commands/results:
docs/audits/verification-log.mdV-114–V-116 - Backend fixtures:
JobTrackerApi.Tests/JobCvMatchServiceTests.cs - Frontend label coverage:
job-tracker-ui/src/match-score-panel.test.tsx - Implementation commit:
da1aa8b
Rollback
Revert da1aa8b. No database downgrade, dependency rollback or cache purge is required. Existing generated learning decisions remain in history; the next request will derive the older term set again.