Understanding regression failures through test-passing and test-failing code changes

Debugging and isolating changes responsible for regression test failures are some of the most challenging aspects of modern software development. Automatic bug localization techniques reduce the manual effort developers spend examining code, for example, by focusing attention on the minimal subset of recent changes that results in the test failure, or on changes to components with most dependencies or highest churn. We observe that another subset of changes is worth the developers´ attention: the complement of the maximal set of changes that does not produce the failure. While for simple, independent source-code changes, existing techniques localize the failure cause to a small subset of those changes, we find that when changes interact, the failure cause is often in our proposed subset and not in the subset existing techniques identify. In studying 45 regression failures in a large, open-source project, we find that for 87% of those failures, the complement of the maximal passing set of changes is different from the minimal failing set of changes, and that for 78% of the failures, our technique identifies relevant changes ignored by existing work. These preliminary results suggest that combining our ideas with existing techniques, as opposed to using either in isolation, can improve the effectiveness of bug localization tools.