Researchers have recently achieved significant advances in deep learning techniques,
which in turn has substantially advanced other research disciplines, such as natural …

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 …

Fault Localization (FL) aims to automatically localize buggy lines of code, a key first step in
many manual and automatic debugging tasks. Previous FL techniques assume the provision …

Automatic program understanding and generation techniques could significantly advance
the productivity of programmers and have been widely studied by academia and industry …

Memory-related vulnerabilities constitute severe threats to the security of modern software.
Despite the success of deep learning-based approaches to generic vulnerability detection …

Large Language Models (LLMs) have shown promise in multiple software engineering tasks
including code generation, program repair, code summarisation, and test generation. Fault …

Automatic software debugging mainly includes two tasks of fault localization and automated
program repair. Compared with the traditional spectrum-based and mutation-based …

Commit messages summarize code changes of each commit in natural language, which
help developers understand code changes without digging into detailed implementations …

Fault Localization (FL) is an essential step during the debugging process. With the strong
capabilities of code comprehension, the recent Large Language Models (LLMs) have …

Unit testing could be used to validate the correctness of basic units of the software system
under test. To reduce manual efforts in conducting unit testing, the research community has …