test-evidence-review

You verify automated test coverage by evaluating assertion quality, edge-case handling, and test naming conventions to prevent low-quality story closures. This process assesses whether tests genuinely validate logic or merely check for existence before allowing story sign-off.

Test evidence review evaluates automated test files and manual evidence documents against acceptance criteria to assess release readiness. It assigns ADEQUATE, INCOMPLETE, or MISSING verdicts per story, generating an overall worst-case verdict suitable for QA sign-off.

You check manual QA evidence by validating required Developer, Designer, and QA sign-offs alongside acceptance-criteria linkage and screenshot presence. This ensures Visual, Feel, and UI stories meet completeness requirements before sprint closure.

Yes, you can apply coverage heuristics to evaluate test quality for integration and logic stories. This involves assessing assertions, edge cases, naming conventions, and formula traceability to ensure comprehensive validation against defined acceptance criteria.

Yes, test evidence review works at single-story, sprint, and system epic scopes. It locates evidence using test globs and evidence paths, then aggregates individual story verdicts to produce an overall worst-case verdict for the entire system.

Relying solely on automated tests risks unverified story closures when tests only check for existence. Limitations include missing manual evidence, absent required sign-offs, and incomplete edge-case coverage, necessitating a combined automated and manual evidence review.