Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

This paper provides a comprehensive review of the literature concerning the utilization of
Natural Language Processing (NLP) techniques, with a particular focus on transformer …

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 …

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

During Automated Program Repair (APR), it can be challenging to synthesize correct
patches for real-world systems in general-purpose programming languages. Recent Large …

Language models have outpaced our ability to evaluate them effectively, but for their future
development it is essential to study the frontier of their capabilities. We find real-world …

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 …