Optimization is Better than Generation: Optimizing Commit Message Leveraging Human-written Commit Message

Fuente: arXiv
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Autori principali: Li, Jiawei, Faragó, David, Petrov, Christian, Ahmed, Iftekhar
Natura: Preprint
Pubblicazione: 2025
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author Li, Jiawei
Faragó, David
Petrov, Christian
Ahmed, Iftekhar
author_facet Li, Jiawei
Faragó, David
Petrov, Christian
Ahmed, Iftekhar
contents Commit messages are crucial in software development, supporting maintenance tasks and communication among developers. While Large Language Models (LLMs) have advanced Commit Message Generation (CMG) using various software contexts, some contexts developers consider are often missed by CMG techniques and can't be easily retrieved or even retrieved at all by automated tools. To address this, we propose Commit Message Optimization (CMO), which enhances human-written messages by leveraging LLMs and search-based optimization. CMO starts with human-written messages and iteratively improves them by integrating key contexts and feedback from external evaluators. Our extensive evaluation shows CMO generates commit messages that are significantly more Rational, Comprehensive, and Expressive while outperforming state-of-the-art CMG methods and human messages 88.2%-95.4% of the time.
format Preprint
id arxiv_https___arxiv_org_abs_2501_09861
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimization is Better than Generation: Optimizing Commit Message Leveraging Human-written Commit Message
Li, Jiawei
Faragó, David
Petrov, Christian
Ahmed, Iftekhar
Software Engineering
Commit messages are crucial in software development, supporting maintenance tasks and communication among developers. While Large Language Models (LLMs) have advanced Commit Message Generation (CMG) using various software contexts, some contexts developers consider are often missed by CMG techniques and can't be easily retrieved or even retrieved at all by automated tools. To address this, we propose Commit Message Optimization (CMO), which enhances human-written messages by leveraging LLMs and search-based optimization. CMO starts with human-written messages and iteratively improves them by integrating key contexts and feedback from external evaluators. Our extensive evaluation shows CMO generates commit messages that are significantly more Rational, Comprehensive, and Expressive while outperforming state-of-the-art CMG methods and human messages 88.2%-95.4% of the time.
title Optimization is Better than Generation: Optimizing Commit Message Leveraging Human-written Commit Message
topic Software Engineering
url https://arxiv.org/abs/2501.09861