Test Coverage

Test coverage analysis identifies untested files, partially covered functions, and specific uncovered lines. It evaluates test-to-code ratio, assertion density, and test independence to pinpoint exactly where your code validation is insufficient.

Yes, you can measure line, branch, and function coverage percentages using pytest for Python and Jest for JavaScript. It calculates these metrics and provides detailed reporting to assess your test suite quality and identify untested code paths.

The best way to identify untested files is by analyzing code coverage metrics to pinpoint gaps and assess quality. This provides actionable insights for improving test suites, ensuring all critical paths and edge cases are covered to prevent regressions.

No specific dependencies are required to use this test coverage analysis. It operates independently to evaluate your test-to-code ratio, assertion density, and test independence, providing actionable insights without needing external setup tools.

To run a quick coverage check, you can analyze the project and report any files with less than 80% coverage. This workflow guidance helps you rapidly identify under-tested areas and prioritize improvements for your test suite.