Enhancing Automated Program Repair with Solution Design

Jiuang Zhao, Donghao Yang, Li Zhang, Xiaoli Lian, Zitian Yang, Fang Liu

Abstract

Automatic Program Repair (APR) endeavors to autonomously rectify issues within specific projects, which generally encompasses three categories of tasks: bug resolution, new feature development, and feature enhancement. Despite extensive research proposing various methodologies, their efficacy in addressing real issues remains unsatisfactory. It's worth noting that, typically, engineers have design rationales (DR) on solution--- planed solutions and a set of underlying reasons---before they start patching code. In open-source projects, these DRs are frequently captured in issue logs through project management tools like Jira. This raises a compelling question: How can we leverage DR scattered across the issue logs to efficiently enhance APR?

BibTeX

@inproceedings{Zhao-al:ASE24,
  author    = {Jiuang Zhao and
               Donghao Yang and
               Li Zhang and
               Xiaoli Lian and
               Zitian Yang and
               Fang Liu},
  title     = {Enhancing Automated Program Repair with Solution Design},
  booktitle = {ASE},
  pages     = {1706--1718},
  publisher = {{ACM}},
  year      = {2024},
}

Enhancing Automated Program Repair with Solution Design

Abstract

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