Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied 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 …

Large language models (LLMs) pretrained on vast source code have achieved prominent
progress in code intelligence. However, existing code LLMs have two main limitations in …

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 …

Abstract Large Language Models (LLMs) have drawn widespread attention and research
due to their astounding performance in text generation and reasoning tasks. Derivative …

Pre-trained Generative Language models (eg, PLBART, CodeT5, SPT-Code) for source
code yielded strong results on several tasks in the past few years, including code generation …

Automated code generation can be a powerful technique for software development,
significantly reducing developers' efforts and time required to create new code by generating …

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

While a large number of pre-trained models of source code have been successfully
developed and applied to a variety of software engineering (SE) tasks in recent years, our …

In this work we systematically review the recent advancements in software engineering with
language models, covering 70+ models, 40+ evaluation tasks, 180+ datasets, and 900 …