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When a developer pushes a change to an application's codebase, a goodpractice is to have a test case specifying this behavioral change. Thanks tocontinuous integration (CI), the test is run on subsequent commits to checkthat they do no introduce a regression for that behavior. In this paper, wepropose an approach that detects behavioral changes in commits. As input, ittakes a program, its test suite, and a commit. Its output is a set of testmethods that capture the behavioral difference between the pre-commit andpost-commit versions of the program. We call our approach DCI (Detectingbehavioral changes in CI). It works by generating variations of the existingtest cases through (i) assertion amplification and (ii) a search-basedexploration of the input space. We evaluate our approach on a curated set of 60commits from 6 open source Java projects. To our knowledge, this is the firstever curated dataset of real-world behavioral changes. Our evaluation showsthat DCI is able to generate test methods that detect behavioral changes. Ourapproach is fully automated and can be integrated into current developmentprocesses. The main limitations are that it targets unit tests and works on arelatively small fraction of commits. More specifically, DCI works on commitsthat have a unit test that already executes the modified code. In practice,from our benchmark projects, we found 15.29% of commits to meet the conditionsrequired by DCI.

An Approach and Benchmark to Detect Behavioral Changes of Commits in Continuous Integration