Quality Metrics and Test Reporting
Defining, computing, and communicating software quality. Covers choosing meaningful quality and test metrics (defect escape rate, defect detection effectiveness, defect density, MTTD/MTTR, pass rate, regression frequency, automation suite health and maintenance cost) versus vanity numbers; baselining, trend interpretation (real change versus normal variation), and alert thresholds; dashboards, weekly stability reports, and release-quality reports for engineering, product, and executive audiences, including composite go/no-go scores; framing unfavourable results; guarding against gamed metrics and reading what numbers such as code coverage or a high pass rate hide; investigating contradictory or shifting metrics and testing whether a quality signal really predicts customer outcomes; metric definitions, ownership, and governance; computing metrics from test-run and bug-tracker data (SQL and scripts); designing test-results reporting pipelines, storage schemas, real-time versus batch reporting, alerting, and failure fingerprinting and grouping for triage; and tying quality signals to product and business outcomes. Deciding what to automate and diagnosing individual flaky tests are covered elsewhere.
