Usage, costs, and benefits of continuous integration in open-source projects
Open accessAbstract
Continuous integration (CI) systems automate the compilation, building, and testing of software. Despite CI rising as a big success story in automated software engineering, it has received almost no attention from the research community. For example, how widely is CI used in practice, and what are some costs and benefits associated with CI? Without answering such questions, developers, tool builders, and researchers make decisions based on folklore instead of data. In this paper, we use three complementary methods to study the usage of CI in open-source projects. To understand which CI systems developers use, we analyzed 34,544 open-source projects from GitHub. To understand how developers use CI, we analyzed 1,529,291 builds from the most commonly used CI system. To understand why projects use or do not use CI, we surveyed 442 developers. With this data, we answered several key questions related to the usage, costs, and benefits of CI. Among our results, we show evidence that supports the claim that CI helps projects release more often, that CI is widely adopted by the most popular projects, as well as finding that the overall percentage of projects using CI continues to grow, making it important and timely to focus more research on CI.
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A 2016 survey found that 40% of the 34,000 most popular F/OSS projects on GitHub use CI, rising to 70% among the 500 most popular projects.
“A 2016 survey found that 40% of the 34,000 most popular F/OSS projects on GitHub use CI, rising to 70% when examining the 500 most popular projects.[63]”
From The Labor of Maintaining and Scaling Free and Open-Source Software Projects (2021) · cites this paper as [63]
The Methodology describes a breadth corpus of 34,544 GitHub open-source projects, and RQ1 reports that 40% used CI. The “CI usage by project popularity” section reports 70% usage in the most popular group, but that group contained around 540 projects, not the specified 500. The paper also calls its CI-usage estimates a lower bound because some services could not be detected. (LLM, conf=0.85)
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References 30 · Cited by 342
- Authors
- Hilton, M., Tunnell, T., Huang, K., Marinov, D., & Dig, D.
- Affiliations
- Oregon State University (US)
- University of Illinois Urbana-Champaign (US)
- Venue
- Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering
- Publisher
- ACM
- Published
- 2016-08-25
- Pages
- 426-437
- OpenAlex
- W2347053969
- Semantic Scholar
- 7f099e5bdae86cdb01d4a1da5678f493ac7266d1
- Cited by
- 342
- References
- 30
- Citations by year
- 2026: 32 · 2025: 33 · 2024: 41 · 2023: 34 · 2022: 43 · 2021: 38 · 2020: 29 · 2019: 37 · 2018: 32 · 2017: 20 · 2016: 3
- FWCI
- 26.06
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- IEEE/ACM International Conference on Automated Software Engineering (ASE) (publishedVersion)
- Funders
- National Science Foundation (CCF- 1421503, CCF-1439957, CCF-1553741)
- 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, open source software, test automation, developer survey, GitHub
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