Characterize Software Release Notes of GitHub Projects: Structure, Writing Style, and Content


Release notes (RNs) summarize important changes between two successive software releases to facilitate software upgrades and serve as means of communication between software and its users. However, existing research has shown that many users cannot extract the information they want from RNs effectively and efficiently due to poor structure and insufficient content. Many efforts have been devoted to categorizing documented information in RNs, however, how exactly RNs are organized, in what way RNs are written, and what is written in RNs with respect to project domains and release types remain under investigation. To bridge this knowledge gap, we manually analyzed 612 RNs from 233 top popular GitHub projects to characterize their Structure, Writing Style, and Content. We find 64.54% of RNs organize changes into hierarchical structures following three strategies, i.e., by Change Type, Affected Module, or Change Priority. And 11.60% of RNs adopt multiple strategies to present the changes. Among the three strategies to organize changes, by Change Type is mostly adopted. RNs of major releases and System Software are more likely to organize changes by Affected Module. We also find three types of Writing Styles: Expository, Descriptive, and Persuasive with increasing explanation information and manual effort, taking 30.07%, 34.80%, and 35.13% of RNs, respectively. 83.10% of RNs in System Software projects adopt the Descriptive and Persuasive writing style. For Content, we find System Software and Libraries & Frameworks projects are more likely to record Breaking Changes, while Software Tools projects emphasize Enhancements. Besides, Fixed Bugs and Security Changes are less common in RNs of major releases. Our findings not only serve practitioners with a roadmap for customizing high-quality RNs but also shed light on future research on automating RN.

In The 30th IEEE International Conference on Software Analysis, Evolution and Reengineering
Kai Gao
Kai Gao
Ph.D. Candidate