Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …

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

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 …

The task of repository-level code completion is to continue writing the unfinished code based
on a broader context of the repository. While for automated code completion tools, it is …

Large language models trained on massive code corpora can generalize to new tasks
without the need for task-specific fine-tuning. In few-shot learning, these models take as …

Although large language models (LLMs) have demonstrated impressive ability in code
generation, they are still struggling to address the complicated intent provided by humans. It …

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

Code completion models have made significant progress in recent years, yet current popular
evaluation datasets, such as HumanEval and MBPP, predominantly focus on code …

Code review is an essential part to software development lifecycle since it aims at
guaranteeing the quality of codes. Modern code review activities necessitate developers …

Code completion, which aims to predict the following code token (s) according to the code
context, can improve the productivity of software development. Recent work has proved that …