When we talk about Code Coverage, many teams set ambitious goals—sometimes aiming for 90% or even 100%. At first glance, it feels like higher coverage must mean higher quality. But in reality, coverage numbers can sometimes be misleading if taken at face value.
Code coverage simply measures how much of your codebase is executed by tests. It doesn’t guarantee that the tests themselves are meaningful. For instance, you could achieve 100% coverage with very shallow tests that don’t validate logic properly. That’s why blindly chasing a number often results in wasted effort instead of stronger software.
The real focus should be on test quality and risk-based coverage. Are the tests covering critical paths? Are edge cases, exceptions, and error-handling scenarios being validated? This is where a thoughtful testing strategy matters more than a percentage.
Tools like automated test equipment help reduce redundant manual work and improve the reliability of coverage. When combined with frameworks that track not just execution but assertion strength, teams can build tests that genuinely add confidence.
Platforms like Keploy take this further by auto-generating test cases and mocks from real API traffic. This means the coverage is closer to how users actually interact with the system, rather than just artificial paths written by developers.