Large Language Models (LLMs) have been gaining increasing attention and demonstrated
promising performance across a variety of Software Engineering (SE) tasks, such as …

Automated Program Repair (APR) attempts to patch software bugs and reduce manual
debugging efforts. Very recently, with the advances in Large Language Models (LLMs), an …

Automated Program Repair (APR) aims to help developers automatically patch software
bugs. However, current state-of-the-art traditional and learning-based APR techniques face …

Automated Program Repair (APR) aims to automatically generate patches for buggy
programs. Recent APR work has been focused on leveraging modern Large Language …

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 …

Due to the promising future of Automated Program Repair (APR), researchers have
proposed various APR techniques, including heuristic-based, template-based, and …

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 …

Automatic program repair (APR) is crucial to improve software reliability. Recently, neural
machine translation (NMT) techniques have been used to automatically fix software bugs …

Automated Program Repair (APR) helps improve the efficiency of software development and
maintenance. Recent APR techniques use deep learning, particularly the encoder-decoder …

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 …