JUPYTER
calculate_distrubution.ipynb (90.41 kB)
JUPYTER
calculate_kappa.ipynb (2.25 kB)
TEXT
parse_GHArichive.py (1.62 kB)
JUPYTER
plot.ipynb (4.6 kB)
ARCHIVE
Plot.zip (399.61 kB)
JUPYTER
Taxonomy.ipynb (13.03 kB)
TEXT
readme.md (1.22 kB)
ARCHIVE
Dataset.zip (262.68 kB)
DATASET
Code_Book.xlsx (22.48 kB)
TEXT
Writing Release Notes for Your Software How to Get it Right.md (7.79 kB)
1/0
[ICPC22] Demystifying Software Release Note Issues on GitHub —— Dataset
Download all (805.69 kB) This item is shared privately
dataset
modified on 2022-03-22, 09:06 Release notes (RNs) summarize main changes between two consecutive software versions and serve as a central source of information when users upgrade software. While producing high quality
RNs can be hard and poses a variety of challenges to developers,
a comprehensive empirical understanding on these challenges is
still lacking. In this paper, we bridge this knowledge gap by manually analyzing 1,731 latest GitHub issues to build a comprehensive
taxonomy of RN issues with four dimensions: Content, Presentation, Accessibility, and Production. Among these issues, nearly half
(48.47%) of them focus on Production; Content, Accessibility, and
Presentation take 25.61%, 17.65%, and 8.27%, respectively. We find
that: 1) RN producers are more likely to miss information than
to include incorrect information, especially for breaking changes;
2) improper layout may bury important information and confuse
users; 3) many users find RNs inaccessible due to link deterioration,
lack of notification, and obfuscate RN locations; 4) automating and
regulating RN production is challenging despite producers’ great
needs. Our taxonomy pictures a roadmap to improve RN production
in practice and reveals interesting future research directions.