Discussions

Many teams chase high code coverage numbers, assuming they directly equate to robust software. However, true code quality lies in understanding what those metrics actually represent. Code coverage measures how much of your codebase is executed during testing, but it doesn’t reveal how well that code has been tested.

For instance, you might achieve 90% coverage but still miss critical edge cases, logic errors, or integration issues that occur in production. That’s why it’s essential to go beyond surface-level metrics and analyze coverage depth—which includes condition coverage, branch testing, and MC/DC coverage for safety-critical systems.

Developers and QA engineers should view code coverage as a diagnostic tool, not a vanity metric. It can highlight untested paths, redundant code, or areas needing refactoring. When integrated into CI/CD pipelines, coverage insights provide continuous visibility into testing health, helping teams make data-driven decisions about code stability.

Ultimately, the goal isn’t just to increase code coverage percentages but to ensure meaningful, risk-based testing that strengthens product reliability and developer confidence.