research-article

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Automatic Core-Developer Identification on GitHub: A Validation Study

Authors:

Mitchell Joblin,

Sven ApelAuthors Info & Claims

ACM Transactions on Software Engineering and Methodology, Volume 32, Issue 6

Article No.: 138, Pages 1 - 29

https://doi.org/10.1145/3593803

Published: 30 September 2023 Publication History

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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.

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Index Terms

Automatic Core-Developer Identification on GitHub: A Validation Study
1. Software and its engineering
  1. Software creation and management
    1. Collaboration in software development
      1. Open source model

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Published In

cover image ACM Transactions on Software Engineering and Methodology

ACM Transactions on Software Engineering and Methodology Volume 32, Issue 6

November 2023

949 pages

ISSN:1049-331X

EISSN:1557-7392

DOI:10.1145/3625557

Editor:
Mauro Pezzè
USI Università della Svizzera italiana and SIT Schaffhausen Institute of Technology, Switzerland

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 September 2023

Online AM: 22 April 2023

Accepted: 15 March 2023

Revised: 03 February 2023

Received: 23 November 2022

Published in TOSEM Volume 32, Issue 6

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Khatoonabadi SAbdellatif ACosta DShihab E(2024)Predicting the First Response Latency of Maintainers and Contributors in Pull RequestsIEEE Transactions on Software Engineering10.1109/TSE.2024.344374150:10(2529-2543)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1109/TSE.2024.3443741
Paradis CKazman RTamburri D(2024)Analyzing the Tower of Babel with KaiauluJournal of Systems and Software10.1016/j.jss.2024.111967210:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111967
Venigalla AChimalakonda S(2024)An exploratory study of software artifacts on GitHub from the lens of documentationInformation and Software Technology10.1016/j.infsof.2024.107425169:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.infsof.2024.107425

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