What is the Truck Factor of popular GitHub applications? A first assessment

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1 Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil
2 Department of Computer Science, Federal University of Piaui, Teresina, Piauí, Brazil
DOI
10.7287/peerj.preprints.1233v3
Published
Accepted
Subject Areas
Social Computing, Software Engineering
Keywords
Truck Factor, Code Authorship, GitHub, Open source software, Agile Programming
Copyright
© 2017 Avelino et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
Cite this article
Avelino G, Valente MT, Hora A. 2017. What is the Truck Factor of popular GitHub applications? A first assessment. PeerJ Preprints 5:e1233v3

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).

Author 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