Search-Based Automated Program Repair: A Survey
Shilong Zhang, Dongcheng Li, Man Zhao, Hui Li, W. Eric Wong · 2024
This paper presents a review of state-of-the-art search-based automated program repair techniques, which are crucial for efficiently and accurately fixing bugs and vulnerabilities in software engineering. Traditional manual repair methods are increasingly seen as inadequate due to their high labor costs and time consumption. The versatility and applicability of search-based techniques have sparked significant interest in the software engineering community, driving a surge in research focused on developing more effective and efficient automated repair methods. The paper begins by introducing the foundational concepts and background of traditional automated program repair. It then delves into a detailed discussion of various search-based techniques and algorithms proposed in recent years. The review summarizes commonly used search-based frameworks, critically analyzing their strengths and limitations. It also provides a comparative analysis of different techniques concerning target languages, datasets, and other relevant aspects. In addition to evaluating current methodologies, the paper identifies ongoing challenges in the field and suggests potential directions for future research. By offering a thorough and systematic overview, this review aims to provide valuable insights and guidance for advancing the development and implementation of search-based automated program repair techniques.