Quality and productivity outcomes relating to continuous integration in GitHub
Abstract
Software processes comprise many steps; coding is followed by building, integration testing, system testing, deployment, operations, among others. Software process integration and automation have been areas of key concern in software engineering, ever since the pioneering work of Osterweil; market pressures for Agility, and open, decentralized, software development have provided additional pressures for progress in this area. But do these innovations actually help projects? Given the numerous confounding factors that can influence project performance, it can be a challenge to discern the effects of process integration and automation. Software project ecosystems such as GitHub provide a new opportunity in this regard: one can readily find large numbers of projects in various stages of process integration and automation, and gather data on various influencing factors as well as productivity and quality outcomes. In this paper we use large, historical data on process metrics and outcomes in GitHub projects to discern the effects of one specific innovation in process automation: continuous integration. Our main finding is that continuous integration improves the productivity of project teams, who can integrate more outside contributions, without an observable diminishment in code quality.
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Bug-related issues are more severe and widely used in the literature as a proxy for quality.
“Second, since issues can vary in nature and severity, we focus specifically on bug-related issues, which are more severe and widely used in the literature as a proxy for quality (Vasilescu et al. 2015).”
From The Impact of Generative AI on Collaborative Open-Source Software Development: Evidence from GitHub Copilot  (2024) · cites this paper as Vasilescu et al. 2015
Cites
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Cohen (2013) · doi:10.4324/9780203774441 · Cited by 3,228 · see citing works
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Usage, 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 · see citing works
Song, F., Agarwal, A., & Wen, W. (2024) · SSRN Electronic Journal (preprint) · doi:10.2139/ssrn.4856935 · Cited by 30 · see citing works
- Authors
- Vasilescu, B., Yu, Y., Wang, H., Devanbu, P., & Filkov, V.
- Affiliations
- University of California, Davis (US)
- National University of Defense Technology (CN)
- University of California at Davis, USA
- Venue
- Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering
- Publisher
- ACM
- Published
- 2015-08-30
- Pages
- 805-816
- OpenAlex
- W2040915209
- Cited by
- 406
- References
- 1
- Citations by year
- 2026: 38 · 2025: 30 · 2024: 33 · 2023: 35 · 2022: 35 · 2021: 43 · 2020: 57 · 2019: 51 · 2018: 41 · 2017: 29 · 2016: 14
- FWCI
- 24.23
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE) (publishedVersion)
- Funders
- National Science Foundation (1247280, 1414172)
- National Natural Science Foundation of China (61432020, 61472430)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Science Applications › Open Source Software Innovations
- Keywords
- continuous integration, software process automation, software quality, software productivity, GitHub, open source software, code quality, integration testing
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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.
Statistics and arithmetic are recomputed, not judged.
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