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

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) 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 …

There is burgeoning interest in designing AI-based systems to assist humans in designing
computing systems, including tools that automatically generate computer code. The most …

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 …

Human developers can produce code with cybersecurity bugs. Can emerging 'smart'code
completion tools help repair those bugs? In this work, we examine the use of large language …

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 …