PYURIFY:
Purifying Python Tests for Precise Fault Localization

Summary

Statistical fault localization (SFL) techniques use test coverage to rank suspicious program elements. However, they often suffer from low precision when tests contain multiple assertions or unrelated code that obscures the relationship between test outcomes and faulty code. Test case purification addresses this problem by transforming complex test cases into simplified, single-assertion variants. We present PYURIFY, a tool that implements test case purification for Python through two steps: first, atomization splits each test with multiple assertions into separate single-assertion tests; second, dynamic program slicing removes code irrelevant to each assertion. This purification process produces cleaner test spectra, enabling SFL techniques to pinpoint faulty code more accurately. PYURIFY provides both a command-line interface and a Python API for seamless integration with existing testing and fault localization workflows. Our evaluation of real Python bugs demonstrates that test case purification consistently improves fault localization accuracy.