mutation-testing

Mutation testing identifies blind spots in a Python test suite by introducing small code changes and verifying that tests fail when catching them. This mechanism exposes untested code paths and weak assertions to improve coverage and confidence.

To run mutation testing on a Python project using pytest, configure mutmut settings in setup.cfg or pyproject.toml. The tool generates mutants, evaluates whether your tests detect the changes, and tracks which tests kill them to guide improvements.

Yes, you can integrate mutation testing into CI pipelines to routinely validate test effectiveness during development and releases. It uses mutmut and pytest to automate mutant generation and evaluate test detection capabilities.

To run mutation testing with mutmut, you need a configured test layout with a tests directory and a src package, plus mutmut settings in setup.cfg or pyproject.toml. The workflow requires mutmut and pytest installed to evaluate test effectiveness.

Standard test coverage measures executed code lines, while mutation testing modifies code to verify if tests actually catch behavioral changes. Mutation testing provides a deeper quality assessment by exposing weak assertions and untested logic that standard coverage misses.