Leveraging Models to Reduce Test Cases in Software Repositories

@article{Gharachorlu2021LeveragingMT,
  title={Leveraging Models to Reduce Test Cases in Software Repositories},
  author={Golnaz Gharachorlu and Nick Sumner},
  journal={2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)},
  year={2021},
  pages={230-241}
}
  • Golnaz Gharachorlu, Nick Sumner
  • Published 22 March 2021
  • Computer Science
  • 2021 IEEE/ACM 18th International Conference on Mining Software Repositories (MSR)
Given a failing test case, test case reduction yields a smaller test case that reproduces the failure. This process can be time consuming due to repeated trial and error with smaller test cases. Current techniques speed up reduction by only exploring syntactically valid candidates, but they still spend significant effort on semantically invalid candidates. In this paper, we propose a model-guided approach to speed up test case reduction. The approach trains a model of semantic properties driven… 
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TLDR
This work explores the possibility that good test case reduction can be achieved without revisiting, yielding an O(n) algorithm, and shows that on a suite of large fuzzer-generated test cases for compilers, the O( n) approach yields reduced test cases with similar size, while decreasing the reduction time by 65% on average.
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