Code coverage is one of the most widely used metrics in quality gates, but it is also one of the most misunderstood. To use coverage wisely, QA engineers need to know what it measures, what it does not, and how to combine it with other signals.
Understanding Coverage Metrics and Their Limits
Coverage tools measure how much of the code was executed by tests, often reporting line, branch or function coverage percentages. High coverage suggests that many paths are exercised, but it does not guarantee that tests are meaningful or that important behaviours are verified.
Examples of coverage metrics:
- Line coverage: fraction of lines executed at least once
- Branch coverage: fraction of decision branches taken
- Mutation score: fraction of injected code changes caught by testsUsed well, coverage helps you spot blind spots and guide where to invest in additional tests.
Common Mistakes
Mistake 1 — Equating high coverage with high quality
This oversimplifies reality.
❌ Wrong: Assuming 90% coverage automatically means the system is well tested.
✅ Correct: Combine coverage with test reviews, defect history and risk analysis.
Mistake 2 — Ignoring coverage on new or changed code
This misses regressions.
❌ Wrong: Only tracking overall project coverage, which may move slowly.
✅ Correct: Use “coverage on new code” as a gate so changes bring their own tests.