Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

Research at the intersection of machine learning, programming languages, and software
engineering has recently taken important steps in proposing learnable probabilistic models …

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 help developers improve software reliability by
generating patches for buggy programs. Although many code language models (CLM) are …

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 …

Software development life cycle is profoundly influenced by bugs; their introduction,
identification, and eventual resolution account for a significant portion of software …

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

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

Unit tests play a key role in ensuring the correctness of software. However, manually
creating unit tests is a laborious task, motivating the need for automation. Large Language …