Quantify QA performance with mathematical precision. Our engine validates inputs to ensure your executive reports are 100% accurate.
Industry Standard Normalization Applied
Waiting for Test Execution to begin...
In high-growth engineering teams, "Done" is not a status—Quality is. This guide explores how to use our Free QA Metrics Calculator to drive data-backed release decisions and optimize your testing lifecycle.
Our calculator uses a Multi-Gate Normalization Algorithm. It creates a hierarchy of dependencies: if test execution is zero, it prevents the pass rate from skewing. It validates that "Passed + Failed" cannot exceed "Executed," ensuring your reports remain mathematically sound and professional.
Removing subjectivity from QA is vital. Instead of "testing is going well," you provide a 92% Success Rate. This transparency builds trust with stakeholders and allows for precise bottleneck identification in the STLC.
| Metric Name | Calculation Logic | Healthy Range |
|---|---|---|
| Test Pass Rate | (Passed / Executed) * 100 | > 95% |
| Defect Rejection Ratio | (Rejected / Raised) * 100 | < 5% |
Data: Execution 95% (Healthy), but Pass Rate 60% (Critical).
Meaning: The QA team is finishing all tasks, but the software is failing every second test. You should NOT release this build. Our tool identifies this mismatch instantly.
Integrity matters. 0% execution means no testing has occurred. Without data, quality is unknown. Our engine prevents "Healthy" signals until a significant portion of execution is completed.
The tool highlights fields in red if you enter impossible data (e.g., Executed > Total). Check the Insight Box for specific corrections required to validate your report.