A Topological Analysis of the Open Souce Software Development Community

The fast growth of OSS has increased the interest in studying the composition of the OSS community and its collaboration mechanisms. Moreover, the success of a project may be related to the underlying social structure of the OSS development community. In this paper, we perform a quantitative analysis of Open Source Software developers by studying the entire development community at SourceForge. Statistics and social network properties are explored to find collaborations and the effects of different members in the OSS development community. Small world phenomenon and scale free behaviors are found in the SourceForge development network. These topological properties may potentially explain the success and efficiency of OSS development practices. We also infer from our analysis that weakly associated but contributing co-developers and active users may be an important factor in OSS development.

[1]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[2]  W. Powell,et al.  Network Dynamics and Field Evolution: The Growth of Interorganizational Collaboration in the Life Sciences1 , 2005, American Journal of Sociology.

[3]  Greg Madey,et al.  Understanding OSS as a Self-Organizing Process , 2002 .

[4]  Jane Greenberg,et al.  Who is an open source software developer? , 2002, CACM.

[5]  R. Gulati,et al.  Where Do Interorganizational Networks Come From?1 , 1999, American Journal of Sociology.

[6]  Albert-László Barabási,et al.  Internet: Diameter of the World-Wide Web , 1999, Nature.

[7]  Brian Fitzgerald,et al.  Understanding open source software development , 2002 .

[8]  Kouichi Kishida,et al.  Evolution patterns of open-source software systems and communities , 2002, IWPSE '02.

[9]  G. Madey,et al.  A MULTI-MODEL DOCKING EXPERIMENT OF DYNAMIC SOCIAL NETWORK SIMULATIONS , 2003 .

[10]  Alexander Hars,et al.  Working for free? Motivations of participating in open source projects , 2001, Proceedings of the 34th Annual Hawaii International Conference on System Sciences.

[11]  M. Newman.  Clustering and preferential attachment in growing networks. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Jin Xu,et al.  A RESEARCH SUPPORT SYSTEM FRAMEWORK FOR WEB DATA MINING , 2004 .

[13]  Sharon L. Milgram,et al.  The Small World Problem , 1967 .

[14]  Jin Xu.  A Docking Experiment : Swarm and Repast for Social Network Modeling , 2003 .

[15]  David Bollier,et al.  The Power of Openness Why Citizens, Education, Government and Business Should Care About the Coming Revolution in Open Source Code Software , 1999 .

[16]  S H Strogatz,et al.  Random graph models of social networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Kevin Crowston,et al.  AN EXPLORATORY STUDY OF OPEN SOURCE SOFTWARE DEVELOPMENT TEAM STRUCTURE , 2002 .

[18]  Michel Grossetti,et al.  Markets from Networks. Socioeconomic Models of Production , 2003 .

[19]  Walt Scacchi,et al.  Data Mining for Software Process Discovery in Open Source Software Development Communities , 2004, MSR.

[20]  M. Lynn.  Hawaii International Conference on System Sciences , 1996 .

[21]  Neng Xu.  An exploratory study of open source software based on public project archives , 2003 .

[22]  Greg Madey,et al.  THE OPEN SOURCE SOFTWARE DEVELOPMENT PHENOMENON: AN ANALYSIS BASED ON SOCIAL NETWORK THEORY , 2002 .

[23]  Steven B. Andrews,et al.  Structural Holes: The Social Structure of Competition , 1995, The SAGE Encyclopedia of Research Design.

[24]  B. Uzzi,et al.  The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect , 1996 .

[25]  Jesús M. González-Barahona,et al.  Applying Social Network Analysis to the Information in CVS Repositories , 2004, MSR.

[26]  John Scott.  What is social network analysis , 2010 .

[27]  Yongqin Gao,et al.  Analysis and Modeling of the Open Source Software Community , 2003 .

[28]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[29]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[30]  Kevin Crowston,et al.  Defining Open Source Software Project Success , 2003, ICIS.

[31]  Steve McConnell,et al.  Software Engineering Principles , 1999, IEEE Software.

[32]  Georg von Krogh,et al.  Open Source Software and the "Private-Collective" Innovation Model: Issues for Organization Science , 2003, Organ. Sci..

[33]  Kevin Crowston,et al.  The Perils and Pitfalls of Mining SourceForge , 2004, MSR.