SOTAVerified

RNSum: A Large-Scale Dataset for Automatic Release Note Generation via Commit Logs Summarization

2022-05-01ACL 2022Unverified0· sign in to hype

Hisashi Kamezawa, Noriki Nishida, Nobuyuki Shimizu, Takashi Miyazaki, Hideki Nakayama

Unverified — Be the first to reproduce this paper.

Reproduce

Abstract

A release note is a technical document that describes the latest changes to a software product and is crucial in open source software development. However, it still remains challenging to generate release notes automatically. In this paper, we present a new dataset called RNSum, which contains approximately 82,000 English release notes and the associated commit messages derived from the online repositories in GitHub. Then, we propose classwise extractive-then-abstractive/abstractive summarization approaches to this task, which can employ a modern transformer-based seq2seq network like BART and can be applied to various repositories without specific constraints. The experimental results on the RNSum dataset show that the proposed methods can generate less noisy release notes at higher coverage than the baselines. We also observe that there is a significant gap in the coverage of essential information when compared to human references. Our dataset and the code are publicly available.

Tasks

Reproductions