ABSTRACT
Social coding paradigm is reshaping the distributed software development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. Various kinds of social networks are formed based on social activities among developers. Why this new paradigm can achieve such a great success in attracting external developers, and how they are connected in such a massive community, are interesting questions for revealing power of social coding paradigm. In this paper, we firstly compare the growth curves of project and user in GitHub with three traditional open source software communities to explore differences of their growth modes. We find an explosive growth of the users in GitHub and introduce the Diffusion of Innovation theory to illustrate intrinsic sociological basis of this phenomenon. Secondly, we construct follow-networks according to the follow behaviors among developers in GitHub. Finally, we present four typical social behavior patterns by mining follow-networks containing independence-pattern, group-pattern, star-pattern and hub-pattern. This study can provide several instructions of crowd collaboration to newcomers. According to the typical behavior patterns, the community manager could design corresponding assistive tools for developers.
- M. Bastian, S. Heymann, and M. Jacomy. Gephi: an open source software for exploring and manipulating networks. In ICWSM, 2009.Google Scholar
- A. Begel, J. Bosch, and M.-A. Storey. Social networking meets software development: Perspectives from github, msdn, stack exchange, and topcoder. IEEE Software, 30(1):52–66, 2013. Google ScholarDigital Library
- A. Begel, Y. P. Khoo, and T. Zimmermann. Codebook: Discovering and exploiting relationships in software repositories. In Proceedings of the 32Nd ACM/IEEE International Conference on Software Engineering - Volume 1, ICSE ’10, pages 125–134, 2010. Google ScholarDigital Library
- V. D. Blondel, J.-L. Guillaume, R. Lambiotte, and E. Lefebvre. Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10):P10008, 2008.Google ScholarCross Ref
- L. Dabbish, C. Stuart, J. Tsay, and J. Herbsleb. Social coding in github: transparency and collaboration in an open software repository. In Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work, CSCW ’12, pages 1277–1286, 2012. Google ScholarDigital Library
- G. Gousios. The ghtorent dataset and tool suite. In Proceedings of the 10th Working Conference on Mining Software Repositories, MSR ’13, pages 233–236, Piscataway, NJ, USA, 2013. IEEE Press. Google ScholarDigital Library
- G. Gousios, M. Pinzger, and A. v. Deursen. An exploratory study of the pull-based software development model. In Proceedings of the 36th International Conference on Software Engineering, ICSE 2014, pages 345–355, 2014. Google ScholarDigital Library
- G. Gousios and D. Spinellis. Ghtorrent: Github’s data from a firehose. In Mining Software Repositories (MSR), 2012 9th IEEE Working Conference on, pages 12–21, June 2012. Google ScholarDigital Library
- E. M. Rogers. Diffusion of innovations. Simon and Schuster, 2010.Google Scholar
- L. Singer and K. Schneider. Influencing the adoption of software engineering methods using social software. In ICSE, pages 1325–1328, 2012. Google ScholarDigital Library
- M.-A. Storey, C. Treude, A. van Deursen, and L.-T. Cheng. The impact of social media on software engineering practices and tools. In Proceedings of the FSE/SDP workshop on Future of software engineering research, FoSER ’10, pages 359–364, New York, NY, USA, 2010. ACM. Google ScholarDigital Library
- D. Surian, D. Lo, and E.-P. Lim. Mining collaboration patterns from a large developer network. In Reverse Engineering (WCRE), 2010 17th Working Conference on, pages 269–273. IEEE, 2010. Google ScholarDigital Library
- F. Thung, T. F. Bissyande, D. Lo, and L. Jiang. Network structure of social coding in github. In Proceedings of the 2013 17th European Conference on Software Maintenance and Reengineering, CSMR ’13, pages 323–326, Washington, DC, USA, 2013. IEEE Computer Society. Google ScholarDigital Library
- J. Tsay, L. Dabbish, and J. Herbsleb. Influence of social and technical factors for evaluating contribution in github. In Proceedings of the 36th International Conference on Software Engineering, ICSE ’14, pages 356–366, 2014. Google ScholarDigital Library
- B. Vasilescu, V. Filkov, and A. Serebrenik. Stackoverflow and github: Associations between software development and crowdsourced knowledge. In Proceedings of the 2013 International Conference on Social Computing, SOCIALCOM ’13, pages 188–195, 2013. Google ScholarDigital Library
- Y. Yu, H. Wang, G. Yin, X. Li, and C. Yang. Hesa: The construction and evaluation of hierarchical software feature repository. In SEKE, pages 624–631, 2013.Google Scholar
- Y. Yu, H. Wang, G. Yin, and B. Liu. Mining and recommending software features across multiple web repositories. In Proceedings of the 5th Asia-Pacific Symposium on Internetware, Internetware ’13, pages 9:1–9:9, 2013. Google ScholarDigital Library
Index Terms
- Exploring the patterns of social behavior in GitHub
Recommendations
Network Structure of Social Coding in GitHub
CSMR '13: Proceedings of the 2013 17th European Conference on Software Maintenance and ReengineeringSocial coding enables a different experience of software development as the activities and interests of one developer are easily advertised to other developers. Developers can thus track the activities relevant to various projects in one umbrella site. ...
Investigating Homophily in Online Social Networks
WI-IAT '10: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01Similarity breeds connections, the principle of homophily, has been well studied in existing sociology literature. %Several studies have observed this phenomena by conducting surveys on human subjects. These studies have concluded that new ties are ...
Recommending relevant projects via user behaviour: an exploratory study on github
CrowdSoft 2014: Proceedings of the 1st International Workshop on Crowd-based Software Development Methods and TechnologiesSocial coding sites (e.g., Github) provide various features like Forking and Sending Pull-requests to support crowd-based software engineering. When using these features, a large amount of user behavior data is recorded. User behavior data can reflect ...
Comments