In the past decade, research on test-suite-based automatic program repair has grown
significantly. Each year, new approaches and implementations are featured in major …

Abstract Automated Program Repair (APR) has attracted significant attention from software
engineering research and practice communities in the last decade. Several teams have …

Large language models such as Codex, have shown the capability to produce code for
many programming tasks. However, the success rate of existing models is low, especially for …

Automated generate-and-validate (GV) program repair techniques (APR) typically rely on
hard-coded rules, thus only fixing bugs following specific fix patterns. These rules require a …

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 …

Learning-based fault localization has been intensively studied recently. Prior studies have
shown that traditional Learning-to-Rank techniques can help precisely diagnose fault …

Recent years have seen an explosion of work in automated program repair. While previous
work has focused exclusively on tools for single languages, recent work in multi-language …

Automated program repair is the problem of automatically fixing bugs in programs in order to
significantly reduce the debugging costs and improve the software quality. To address this …

Large language models (LLMs) have demonstrated impressive capabilities across various
natural language processing (NLP) tasks, such as machine translation, question answering …

Benchmarks of bugs are essential to empirically evaluate automatic program repair tools. In
this paper, we present BEARS, a project for collecting and storing bugs into an extensible …