Applying genetic programming with similar bug fix information to automatic fault repair

Geunseok Yang, Youngjun Jeong, Kyeongsic Min, Jung Won Lee, Byungjeong Lee

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Owing to the high complexity of recent software products, developers cannot avoid major/minor mistakes, and software bugs are generated during the software development process. When developers manually modify a program source code using bug descriptions to fix bugs, their daily workloads and costs increase. Therefore, we need a way to reduce their workloads and costs. In this paper, we propose a novel automatic fault repair method by using similar bug fix information based on genetic programming (GP). First, we searched for similar buggy source codes related to the new given buggy code, and then we searched for a fixed the buggy code related to the most similar source code. Next, we transformed the fixed code into abstract syntax trees for applying GP and generated the candidate program patches. In this step, we verified the candidate patches by using a fitness function based on given test cases to determine whether the patch was valid or not. Finally, we produced program patches to fix the new given buggy code.

Original languageEnglish
Article number92
JournalSymmetry
Volume10
Issue number4
DOIs
StatePublished - 1 Apr 2018

Keywords

  • Automatic fault repair
  • Bug fix information
  • Genetic programming
  • Software maintenance

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