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Predicting long-time contributors for GitHub projects using machine learning

  • Published:2021-10 Issue: Volume:138 Page:106616
  • ISSN:0950-5849
  • Container-title:Information and Software Technology
  • language:en
  • Short-container-title:Information and Software Technology

Author:

Eluri Vijaya KumarORCID,Mazzuchi Thomas A.,Sarkani Shahram

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference51 articles.

1. Industry questions about open source software in business: Research directions and potential answers;Ihara,2014

2. Open source software survivability prediction using multi layer perceptron;Eluri,2019

3. Does the initial environment impact the future of developers?;Zhou,2011

4. Understanding developers’ motives in open source projects: A multi-theoretical framework;Benbya;Commun. AIS,2010

5. Motivation of software developers in open source projects: An internet-based survey of contributors to the linux kernel;Hertel;Res. Policy,2003

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1. GlobalTagNet: A Graph-Based Framework for Multi-Label Classification in GitHub Issues;2024 IEEE 32nd International Requirements Engineering Conference (RE);2024-06-24

2. Probabilistic Model Checking GitHub Repositories for Software Project Analysis;Applied Sciences;2024-02-02

3. An Empirical Study of the Apache Voting Process on Open Source Community Governance;Proceedings of the 14th Asia-Pacific Symposium on Internetware;2023-08-04

4. A broad approach to expert detection using syntactic and semantic social networks analysis in the context of Global Software Development;Journal of Computational Science;2023-01

5. Prediction of Survivability for Open-Source with Supervised Machine Learning;The Journal of Korean Institute of Information Technology;2022-12-31
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