Do as I Do, Not as I Say: Do Contribution Guidelines Match the GitHub Contribution Process?
Open accessAbstract
Developer contribution guidelines are used in social coding sites like GitHub to explain and shape the process a project expects contributors to follow. They set standards for all participants and "save time and hassle caused by improperly created pull requests or issues that have to be rejected and re-submitted" (GitHub). Yet, we lack a systematic understanding of the content of a typical contribution guideline, as well as the extent to which these guidelines are followed in practice. Additionally, understanding how guidelines may impact projects that use Continuous Integration as part of the contribution process is of particular interest. To address this knowledge gap, we conducted a mixed-methods study of 53 GitHub projects with explicit contribution guidelines and coded the guidelines to extract key themes. We then created a process model using GitHub activity data (e.g., commit, new issue, new pull request) to compare the actual activity with the prescribed contribution guidelines. We show that approximately 68% of these projects diverge significantly from the expected process.
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The inclusion criterion for GenAI governance was fixed before document analysis began and stayed stable throughout screening, not shaped by findings.
“We fixed this inclusion criterion before document analysis began, building on prior definitions of OSS contribution governance [1, 11, 12]. The criterion stayed stable throughout screening; we only refined how it applied to borderline cases, so it was not shaped by our findings.”
From To Ban or Not to Ban? How Open Source Projects Govern GenAI Contributions (2026) · cites this paper as [12]
Cited by
Sorted by citations
To Ban or Not to Ban? How Open Source Projects Govern GenAI Contributions
Yang, W., He, R., & Zhou, M. (2026) · Proceedings of the 41st IEEE/ACM International Conference on Automated Software Engineering · doi:10.1145/3832783.3837448 · Cited by 1 · see citing works
"We Permit the Use of AI, but [...]": The Landscape of AI Policies in Popular Open Source Projects
Hora, A., Robbes, R., & Zacchiroli, S. (2026) · arXiv · doi:10.48550/arxiv.2609.07542
AI Policy, Disclosure, and Human in the Loop: How Are Contribution Guidelines Adapting to GenAI?
Hora, A., & Robbes, R. (2026) · arXiv · doi:10.48550/arxiv.2605.16706
- Authors
- Elazhary, O., Storey, M.-A., Ernst, N., & Zaidman, A.
- Affiliations
- University of Victoria (CA)
- Delft University of Technology (NL)
- Venue
- 2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)
- Publisher
- IEEE
- Published
- 2019-09
- Pages
- 286-290
- ISSN
- 1063-6773 (ISSN-L)
- OpenAlex
- W2992895209
- Cited by
- 42
- References
- 0
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 7 · 2023: 4 · 2022: 5 · 2021: 9 · 2020: 2 · 2019: 1
- FWCI
- 3.39
- Type
- conference paper
- Language
- en
- Open access
- green
- resolver.tudelft.nl
- Licence
- Locations
- IEEE International Conference on Software Maintenance (ICSM) (publishedVersion)
- UVic’s Research and Learning Repository (University of Victoria) (submittedVersion)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Keywords
- contribution guidelines, GitHub, pull requests, issue tracking, continuous integration, social coding, open source projects, process model, guideline adherence, developer activity
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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