Code intelligence leverages machine learning techniques to extract knowledge from
extensive code corpora, with the aim of developing intelligent tools to improve the quality …

Despite the capability in successfully fixing more and more real-world bugs, existing
Automated Program Repair (APR) techniques are still challenged by the long-standing …

Context: Large language models trained on source code can support a variety of software
development tasks, such as code recommendation and program repair. Large amounts of …

Software comments sometimes are not promptly updated in sync when the associated code
is changed. The inconsistency between code and comments may mislead the developers …

Software is constantly changing, requiring developers to perform several derived tasks in a
timely manner, such as writing a description for the intention of the code change, or …

Good comments are invaluable assets to software projects, as they help developers
understand and maintain projects. However, due to some poor commenting practices …

Representing code changes as numeric feature vectors, ie, code change representations, is
usually an essential step to automate many software engineering tasks related to code …

Software undergoes constant changes to support new requirements, address bugs,
enhance performance, and ensure maintainability. Thus, developers spend a great portion …

Learning-based techniques, especially advanced Large Language Models (LLMs) for code,
have gained considerable popularity in various software engineering (SE) tasks. However …

TODO comments are very widely used by software developers to describe their pending
tasks during software development. However, after performing the task developers …