An Empirical Study on Learning-based Techniques for Explicit and Implicit Commit Messages Generation
Abstract
High-quality and appropriate commit messages help developers to quickly understand and track code evolution, which is crucial for the collaborative development and maintenance of software. To relieve developers of the burden of writing commit messages, researchers have proposed various techniques to generate commit messages automatically, among which learning-based techniques have proven to be promising.
BibTeX
@inproceedings{Huang-al:ASE24,
author = {Zhiquan Huang and
Yuan Huang and
Xiangping Chen and
Xiaocong Zhou and
Changlin Yang and
Zibin Zheng},
title = {An Empirical Study on Learning-based Techniques for Explicit and Implicit Commit Messages Generation},
booktitle = {ASE},
pages = {544--556},
publisher = {{ACM}},
year = {2024},
}