The DOI matches its Crossref record.
The GHTorent dataset and tool suite
Abstract
During the last few years, GitHub has emerged as a popular project hosting, mirroring and collaboration platform. GitHub provides an extensive REST API, which enables researchers to retrieve high-quality, interconnected data. The GHTorent project has been collecting data for all public projects available on Github for more than a year. In this paper, we present the dataset details and construction process and outline the challenges and research opportunities emerging from it.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As a result, integration friction due to textual conflicts is not explicitly captured in most pull request datasets.”
From AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub (2026) · cites this paper as [25]
Citations
Cites
No references could be resolved yet.
Research works printed but not linked: 3
- grigorik, 2012, GitHub Archive
- 10.1109/MSR.2012.6224294 · DOI
- gousios, 2013, An exploration of the pull-based software development model, 4th ACM Symposium on the Foundations of Software Engineering
Cited by
Sorted by citations
An exploratory study of the pull-based software development model
Gousios, G., Pinzger, M., & Deursen, A. V. (2014) · Proceedings of the 36th International Conference on Software Engineering · doi:10.1145/2568225.2568260 · Cited by 628
Self-citationUsage, costs, and benefits of continuous integration in open-source projects
Hilton, M., Tunnell, T., Huang, K., Marinov, D., & Dig, D. (2016) · Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering · doi:10.1145/2970276.2970358 · Cited by 342
AgenticFlict: A Large-Scale Dataset of Merge Conflicts in AI Coding Agent Pull Requests on GitHub
Ogenrwot, D., & Businge, J. (2026) · Proceedings of the 3rd ACM International Conference on AI-Powered Software · doi:10.1145/3805760.3814923
“This approach follows established practices in large-scale mining of GitHub data [17, 26, 48] and aligns with GitHub’s Terms of Service governing code redistribution [21].”
Metadata
- Authors
- Gousios, G.
- Affiliations
- Delft University of Technology (NL)
- Corresponding author
- Gousios, Georgios
- ORCID
- Gousios, Georgios
- Venue
- 2013 10th Working Conference on Mining Software Repositories (MSR)
- Publisher
- IEEE
- Published
- 2013-05
- Pages
- 233-236
- OpenAlex
- W1972386298
- Cited by
- 399
- References
- 0
- Citations by year
- 2026: 38 · 2025: 21 · 2024: 22 · 2023: 24 · 2022: 32 · 2021: 32 · 2020: 37 · 2019: 32 · 2018: 39 · 2017: 36 · 2016: 21 · 2015: 38 · 2014: 27
- FWCI
- 22.97
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Mining Software Repositories (MSR) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Keywords
- GitHub, software repositories, open source software, software engineering data, REST API, dataset construction
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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