# Towards Automatic Generation of Short Summaries of Commits

arXiv: https://arxiv.org/abs/1703.09603 · HTML: https://mlsanity.com/paper/1703.09603/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2017.

## Built on by (most cited first, 8 of 8)

- [A Survey on Machine Learning Techniques for Source Code Analysis](https://mlsanity.com/paper/2110.09610/) (2021)
- [On the Evaluation of Commit Message Generation Models: An Experimental Study](https://mlsanity.com/paper/2107.05373/) (2021)
- [CommitBERT: Commit Message Generation Using Pre-Trained Programming Language Model](https://mlsanity.com/paper/2105.14242/) (2021)
- [From Commit Message Generation to History-Aware Commit Message Completion](https://mlsanity.com/paper/2308.07655/) (2023)
- [From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence](https://mlsanity.com/paper/2511.18538/) (2025)
- [AutoTSG: Learning and Synthesis for Incident Troubleshooting](https://mlsanity.com/paper/2205.13457/) (2022)
- [CommitBench: A Benchmark for Commit Message Generation](https://mlsanity.com/paper/2403.05188/) (2024)
- [A Sketch-Based Neural Model for Generating Commit Messages from Diffs](https://mlsanity.com/paper/2104.04087/) (2021)

## Abstract (arXiv)

Committing to a version control system means submitting a software change to the system. Each commit can have a message to describe the submission. Several approaches have been proposed to automatically generate the content of such messages. However, the quality of the automatically generated messages falls far short of what humans write. In studying the differences between auto-generated and human-written messages, we found that 82% of the human-written messages have only one sentence, while the automatically generated messages often have multiple lines. Furthermore, we found that the commit messages often begin with a verb followed by an direct object. This finding inspired us to use a "verb+object" format in this paper to generate short commit summaries. We split the approach into two parts: verb generation and object generation. As our first try, we trained a classifier to classify a diff to a verb. We are seeking feedback from the community before we continue to work on generating direct objects for the commits.