Automated program repair (APR) aims to fix software bugs automatically and plays a crucial
role in software development and maintenance. With the recent advances in deep learning …

The advancements in machine learning techniques have encouraged researchers to apply
these techniques to a myriad of software engineering tasks that use source code analysis …

With the proven effectiveness of L arge L anguage M odels (LLMs) in code-related tasks,
researchers have explored their potential for program repair. However, existing repair …

Concept This paper is a living review on automatic program repair 1. Compared to a
traditional survey, a living review evolves over time. I use a concise bullet-list style meant to …

Automated Program Repair (APR) techniques have shown more and more promising results
in fixing real-world bugs. Despite the effectiveness, APR techniques still face an overfitting …

Automated program repair (APR) faces the challenge of test overfitting, where generated
patches pass validation tests but fail to generalize. Existing methods for patch assessment …

Software is constantly changing, requiring developers to perform several derived tasks in a
timely manner, such as writing a description for the intention of the code change, or …

Automated Program Repair (APR) techniques have drawn wide attention from both
academia and industry. Meanwhile, one main limitation with the current state-of-the-art APR …

Representing code changes as numeric feature vectors, ie, code change representations, is
usually an essential step to automate many software engineering tasks related to code …

Numerous code changes are made by developers in their daily work, and a superior
representation of code changes is desired for effective code change analysis. Recently …