What is the Truck Factor of popular GitHub applications? A first assessment
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Abstract
The Truck Factor designates the minimal number of developers that have to be hit by a truck (or quit) before a project is incapacitated. It can be seen as a measurement of the concentration of information in individual team members. We calculate the Truck Factor for 133 popular GitHub applications, in six languages. To infer the authors of a file we use the Degree-of-Authorship (DOA) metric, which is computed using version history data, and to estimate the Truck Factor, we use a greedy heuristic. Results show that most systems have a small truck factor (46% have Truck Factor=1 and 28% have Truck Factor=2).
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2017. What is the Truck Factor of popular GitHub applications? A first assessment. PeerJ Preprints 5:e1233v3 https://doi.org/10.7287/peerj.preprints.1233v3Author comment
An extended and detailed version of this preprint was accepted at ICPC 2016. Please refer to: Guilherme Avelino, Leonardo Passos, Andre Hora, Marco Tulio Valente. A Novel Approach for Estimating Truck Factors. In 24th International Conference on Program Comprehension (ICPC), pages 1-10, 2016. https://arxiv.org/abs/1604.06766
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Competing Interests
The authors declare that they have no competing interests.
Author Contributions
Guilherme Avelino conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, performed the computation work, reviewed drafts of the paper.
Marco Tulio Valente conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.
Andre Hora conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.
Data Deposition
The following information was supplied regarding data availability:
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Funding
This work was funded by grants from Brazilian National Research Council (CNPq) and Minas Gerais Research Foundation (FAPEMIG). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
