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Volume 34 Issue 2
March  2019
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Bo Guo, Young-Woo Kwon, Myoungkyu Song. Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving Software[J]. Journal of Computer Science and Technology, 2019, 34(2): 416-436. DOI: 10.1007/s11390-019-1917-9
Citation: Bo Guo, Young-Woo Kwon, Myoungkyu Song. Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving Software[J]. Journal of Computer Science and Technology, 2019, 34(2): 416-436. DOI: 10.1007/s11390-019-1917-9
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Decomposing Composite Changes for Code Review and Regression Test Selection in Evolving Software

  • 1 Department of Global Operations, PayPal, Omaha Nebraska 68128, U.S.A.;
    2 School of Computer Science and Engineering, Kyungpook National University, Daegu 702-701, South Korea;
    3 Department of Computer Science, University of Nebraska at Omaha, Omaha 68128, U.S.A.

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  • Author Bio:

    Bo Guo is a software engineer at PayPal at Omaha Nebraska, Omaha, since 2012. He received his Ph.D. degree in information science and technology from University of Nebraska at Omaha, Omaha, in August 2017. His research interests span automated approaches for test description generation and selection with provable guarantee in complex, evolving system models.

  • Corresponding author:

    Myoungkyu Song E-mail: myoungkyu@unomaha.edu

  • Received Date: May 16, 2018
  • Revised Date: January 17, 2019
  • Published Date: March 04, 2019
    Abstract
  • Inspecting and testing code changes typically require a significant amount of developer effort. As a system evolves, developers often create composite changes by mixing multiple development issues, as opposed to addressing one independent issue — an atomic change. Inspecting composite changes often becomes time-consuming and error-prone. To test unrelated edits on composite changes, rerunning all regression tests may require excessive time. To address the problem, we present an interactive technique for change decomposition to support code reviews and regression test selection, called ChgCutter. When a developer specifies code change within a diff patch, ChgCutter partitions composite changes into a set of related atomic changes, which is more cohesive and self-contained regarding the issue being addressed. For composite change inspection, it generates an intermediate program version that only includes a related change subset using program dependence relationships. For cost reduction during regression testing, it safely selects only affected tests responsible for changes to an intermediate version. In the evaluation, we apply ChgCutter to 28 composite changes in four open source projects. ChgCutter partitions these changes with 95.7% accuracy, while selecting affected tests with 89.0% accuracy. We conduct a user study with professional software engineers at PayPal and find that ChgCutter is helpful in understanding and validating composite changes, scaling to industry projects.
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