Automatic Core-Developer Identification on GitHub: A Validation Study

Author:

Bock Thomas1ORCID,Alznauer Nils1ORCID,Joblin Mitchell2ORCID,Apel Sven1ORCID

Affiliation:

1. Saarland University, Saarland Informatics Campus, Germany

2. Siemens AG, and Saarland University, Saarland Informatics Campus, Germany

Abstract

Many open-source software projects are self-organized and do not maintain official lists with information on developer roles. So, knowing which developers take core and maintainer roles is, despite being relevant, often tacit knowledge. We propose a method to automatically identify core developers based on role permissions of privileged events triggered in GitHub issues and pull requests. In an empirical study on 25/GitHub projects, (1) we validate the set of automatically identified core developers with a sample of project-reported developer lists, and (2) we use our set of identified core developers to assess the accuracy of state-of-the-art unsupervised developer classification methods. Our results indicate that the set of core developers, which we extracted from privileged issue events, is sound and the accuracy of state-of-the-art unsupervised classification methods depends mainly on the data source (commit data versus issue data) rather than the network-construction method (directed versus undirected, etc.). In perspective, our results shall guide research and practice to choose appropriate unsupervised classification methods, and our method can help create reliable ground-truth data for training supervised classification methods.

Funder

German Research Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Reference110 articles.

1. An empirical study of integration activities in distributions of open source software

2. Amritanshu Agrawal, Akond Rahman, Rahul Krishna, Alexander Sobran, and Tim Menzies. 2018. We don’t need another hero? The impact of “Heroes” on software development. In Proceedings of the International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP’18). ACM, 245–253.

3. Ban Al-Ani, Matthew J. Bietz, Yi Wang, Erik Trainer, Benjamin Koehne, Sabrina Marczak, David Redmiles, and Rafael Prikladnicki. 2013. Globally distributed system developers: Their trust expectations and processes. In Proceedings of the International Conference on Computer-Supported Cooperative Work (CSCW’13). ACM, 563–574.

4. Empirical Study on the Evolution of Developer Social Networks

5. Christian Bird. 2011. Sociotechnical coordination and collaboration in open source software. In Proceedings of the International Conference on Software Maintenance (ICSM’11). IEEE, 568–573.

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