Understanding the root cause of a defect is critical to isolating and repairing buggy behavior. We present Causal Testing, a newmethod of root-cause analysis that relies on the theory of counterfactual causality to identify a set of executions that likely hold key causal information necessary to understand and repair buggy behavior. Using the Defects4J benchmark, we find that Causal Testing could be applied to 71% of real-world defects, and for 77% of those, it can help developers identify the root cause of the defect. A controlled experiment with 37 developers shows that Causal Testing improves participants' ability to identify the cause of the defect from 80% of the time with standard testing tools to 86% of the time with Causal Testing. The participants report that Causal Testing provides useful information they cannot get using tools such as JUnit. Holmes, our prototype, open-source Eclipse plugin implementation of Causal Testing, is available at http://holmes.cs.umass.edu/.
CITATION STYLE
Johnson, B., Brun, Y., & Meliou, A. (2020). Causal testing: Understanding defects’ root causes. In Proceedings - International Conference on Software Engineering (pp. 87–99). IEEE Computer Society. https://doi.org/10.1145/3377811.3380377
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