ComSum: Commit Messages Summarization and Meaning Preservation

TL;DR

ComSum is a large dataset of 7 million commit messages designed for text summarization, emphasizing meaning preservation over traditional metrics, to improve software documentation tools.

Contribution

The paper introduces ComSum, a novel large-scale dataset for commit message summarization that incorporates meaning preservation evaluation methods.

Findings

Dataset contains 7 million commit messages.

Meaning preservation is proposed as an evaluation metric.

The dataset enhances empirical software engineering research.

Abstract

We present ComSum, a data set of 7 million commit messages for text summarization. When documenting commits, software code changes, both a message and its summary are posted. We gather and filter those to curate developers' work summarization data set. Along with its growing size, practicality and challenging language domain, the data set benefits from the living field of empirical software engineering. As commits follow a typology, we propose to not only evaluate outputs by Rouge, but by their meaning preservation.