test-evidence-review

Assessing test evidence quality involves parsing acceptance criteria and test assertions to locate gaps in coverage, naming, and edge-case handling. It applies glob and grep rules to find test files and manual evidence, generating ADEQUATE, INCOMPLETE, or MISSING verdicts to ensure QA receives reliable proof for story closure.

The best way to audit test quality across a sprint is to apply review rules to the sprint scope, counting and classifying assertions while detecting vacuous tests. It checks naming quality and formula traceability, generating per-story ADEQUATE, INCOMPLETE, or MISSING verdicts with an optional markdown report for milestone quality audits.

Verifying manual evidence freshness requires checking criterion linkage, required sign-offs, and screenshot or walkthrough presence for visual and UI stories. The audit evaluates evidence date freshness to ensure manual proof is current and complete for story closure.

Using glob and grep rules allows you to locate test files and manual evidence documents across single story paths, sprint scopes, or system epics. Discovery and mapping strategies find associated automated tests, enabling evaluation of logic, integration, visual, UI, and config data evidence at any scale.

Test files fail to prove edge case coverage when assertions are thin, vacuous, or missing edge case handling. Reviewing test evidence quality detects these gaps by checking assertion coverage, naming, and formula traceability, producing ADEQUATE, INCOMPLETE, or MISSING verdicts to ensure QA receives reliable proof.

Test evidence review operates without external dependencies or components. It relies on glob and grep rules to locate files, parses acceptance criteria and test assertions, and evaluates edge coverage and manual evidence sign-offs independently, producing verdicts and an optional markdown report.