Code coverage isn’t just a metric—it can be a strategic tool to 
prioritize testing efforts. By analyzing which parts of your codebase 
are untested or lightly tested, QA teams can focus resources on areas 
with the highest risk of defects.

For example, modules with complex logic, multiple conditional branches, 
or critical business functionality should take priority in testing. 
Using coverage data this way ensures that testing time is spent 
efficiently, rather than trying to achieve high percentages across 
low-impact code.

This approach also helps in maintaining test suite health over time, 
making sure tests remain meaningful as applications evolve and new 
features are added. Properly leveraged, code coverage becomes a guide to 
smarter, risk-focused testing rather than just a vanity metric.

For more insights on code coverage and its importance in software 
testing, check this informative article:
https://keploy.io/blog/community/understanding-code-coverage-in-software-testing