<p data-start="188" data-end="437">Code coverage shows how much of an application&rsquo;s code is exercised during testing and helps teams understand where their tests are effective and where gaps exist. It offers a practical way to assess whether important logic paths are being validated.

<p data-start="439" data-end="687">By analyzing code coverage data, teams can prioritize testing in high-risk areas such as core business logic, integrations, and error handling. This is especially useful in large codebases, where manual review alone cannot reveal untested sections.

<p data-start="689" data-end="952">Code coverage should be interpreted in context. High coverage does not automatically mean strong test quality, and low coverage does not always indicate poor testing. The value lies in using coverage data to ask better questions about test effectiveness and risk.



<p data-start="954" data-end="1138" data-is-last-node="" data-is-only-node="">When used alongside automated testing and continuous integration, code coverage supports smarter decision-making, reduces regression risk, and strengthens overall software reliability.