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Surgical teams on GitHub: Modeling performance of GitHub project development processes
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DOI：10.1016/j.infsof.2018.03.010.png)
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Abstract
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Context: Better methods of evaluating process performance of OSS projects can benefit decision makers who consider adoption of OSS software in a company. This article studies the closure of issues (bugs and features) in GitHub projects, which is an important measure of OSS development process performance and quality of support that project users receive from the developer team. Objective: The goal of this article is a better understanding of the factors that affect issue closure rates in OSS projects. Methodology: The GHTorrent repository is used to select a large sample of mature, active OSS projects. Using survival analysis, we calculate short-term, and long-term issue closure rates. We formulate several hypotheses regarding the impact of OSS project and team characteristics, such as measures of work centralization, measures that reflect internal project workflows, and developer social networks measures on issue closure rates. Based on the proposed features and several control features, a model is built that can predict issue closure rate. The model allows to test our hypotheses. Results: We find that large teams that have many project members have lower issue closure rates than smaller teams. Similarly, increased work centralization increases issue closure rates. While desirable social network characteristics have a positive impact on the amount of commits in a project, they do not have significant influence on issue closure. Conclusion: Overall, findings from empirical analysis support the classic notion of Brook's - the surgical team - in the context of OSS project development process performance on GitHub. The model of issue closure rates proposed in this article is a first step towards an improved understanding and prediction of this important measure of OSS development process performance.
Keywords:
Open source software (OSS)
Development process performance
Issue closure rate
Work centralization
Issue workflow
Surgical team
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