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Symmetry 2019, 11(2), 144; https://doi.org/10.3390/sym11020144

Healthy or Not: A Way to Predict Ecosystem Health in GitHub

1
School of Software, Central South University, Changsha 410075, China
2
Department of Information Management, Hunan University of Finance and Economics, Changsha 410075, China
3
Department of Computer Science, Missouri State University, Springfield, MO 65897, USA
4
Department of Computing, School of Computing, Engineering and Built Environment, Glasgow Caledonian University, Glasgow G4 0BA, UK
5
School of Software, Central South University, Changsha 410075, China
*
Author to whom correspondence should be addressed.
Received: 23 December 2018 / Revised: 21 January 2019 / Accepted: 22 January 2019 / Published: 28 January 2019
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Abstract

With the development of open source community, through the interaction of developers, the collaborative development of software, and the sharing of software tools, the formation of open source software ecosystem has matured. Natural ecosystems provide ecological services on which human beings depend. Maintaining a healthy natural ecosystem is a necessity for the sustainable development of mankind. Similarly, maintaining a healthy ecosystem of open source software is also a prerequisite for the sustainable development of open source communities, such as GitHub. This paper takes GitHub as an example to analyze the health condition of open source ecosystem and, also, it is a research area in Symmetry. Firstly, the paper presents the healthy definition of GitHub open source ecosystem health and, then, according to the main components of natural ecosystem health, the paper proposes the health indicators and health indicators evaluation method. Based on the above, the GitHub ecosystem health prediction method is proposed. By analyzing the projects and data collected in GitHub, it is found that, using the proposed evaluation indicators and method, we can analyze the healthy development trend of the GitHub ecosystem and contribute to the stability of ecosystem development. View Full-Text
Keywords: open source software; GitHub; Symmetry; ecosystem health; evaluation method open source software; GitHub; Symmetry; ecosystem health; evaluation method
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Liao, Z.; Yi, M.; Wang, Y.; Liu, S.; Liu, H.; Zhang, Y.; Zhou, Y. Healthy or Not: A Way to Predict Ecosystem Health in GitHub. Symmetry 2019, 11, 144.

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