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 …

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 …

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 …

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 …

Many automated test generation techniques have been developed to aid developers with
writing tests. To facilitate full automation, most existing techniques aim to either increase …