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Causal testing: understanding defects' root causes

Brittany Johnson, Yuriy Brun, Alexandra Meliou

Abstract

Understanding the root cause of a defect is critical to isolating and repairing buggy behavior. We present Causal Testing, a new method 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/.

BibTeX
@inproceedings{Johnson-al:ICSE20,
  author    = {Brittany Johnson and
               Yuriy Brun and
               Alexandra Meliou},
  title     = {Causal testing: understanding defects' root causes},
  booktitle = {ICSE},
  pages     = {87--99},
  publisher = {{ACM}},
  year      = {2020},
}

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