A Tool for the Analysis of Social Networks in Collaborative Software Development

In this article, we present a tool that is designed to investigate the collaboration network between actors in software development groups. Our approach uses data derived from the version control system SVN (subversion) to retrieve the collaboration structures using an elaborate refinement process. The software `SVN Network Analysis Tool' (SVNNAT) aims to reveal the strengths and properties of collaboration ties between the developers in order to analyze their productivity and their quality of work in a given constellation of a software development network. In contrast to an earlier version of SVNNAT, our current approach accounts for the specific structures of programming languages in software code to separate technical artifacts from the information about the actors' collaboration in the development network. The result of the evaluation process is a social network of software developers that can be analyzed using typical indicators of topology properties like betweenness, closeness, and degree centralization. In a further step such network analysis can be used to propose an efficient network structure for developers of newly designed software projects.

[1]  Michael Schwind,et al.  SVNNAT: Measuring Collaboration in Software Development Networks , 2008, 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services.

[2]  Audris Mockus,et al.  Automating the Measurement of Open Source Projects , 2003 .

[3]  Michael Schwind,et al.  Unveiling Collaboration Structures in Software Development Projects , 2008, ECIS.

[4]  R. Ferrer i Cancho,et al.  Scale-free networks from optimal design , 2002, cond-mat/0204344.

[5]  Stefan Koch,et al.  Effort, co‐operation and co‐ordination in an open source software project: GNOME , 2002, Inf. Syst. J..

[6]  Jin Xu,et al.  A Topological Analysis of the Open Souce Software Development Community , 2005, Proceedings of the 38th Annual Hawaii International Conference on System Sciences.

[7]  Ricard V. Solé,et al.  Logarithmic growth dynamics in software networks , 2005, ArXiv.

[8]  Anas N. Al-Rabadi,et al.  A comparison of modified reconstructability analysis and Ashenhurst‐Curtis decomposition of Boolean functions , 2004 .

[9]  Audris Mockus,et al.  An Empirical Study of Speed and Communication in Globally Distributed Software Development , 2003, IEEE Trans. Software Eng..

[10]  Michael Schwind,et al.  Scale-free networks , 2006, Wirtschaftsinf..

[11]  Premkumar T. Devanbu,et al.  Latent social structure in open source projects , 2008, SIGSOFT '08/FSE-16.

[12]  John E. Gaffney,et al.  Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation , 1983, IEEE Transactions on Software Engineering.

[13]  Kazuaki Yamada,et al.  Understanding the nature of collaboration in open-source software development , 2005, 12th Asia-Pacific Software Engineering Conference (APSEC'05).

[14]  Rainer Weinreich,et al.  An environment for cooperative software development realization and implications , 1998, Proceedings of the Thirty-First Hawaii International Conference on System Sciences.

[15]  Eirini Kalliamvakou,et al.  Mediterranean Conference on Information Systems ( MCIS ) 2009 Measuring Developer Contribution From Software Repository Data , 2017 .

[16]  Dirk Draheim,et al.  Analytical Processing of Version Control Data: Towards a Process-Centric Viewpoint , 2003 .

[17]  Harvey Siy,et al.  If your ver-sion control system could talk , 1997 .

[18]  Paul Erdös,et al.  On random graphs, I , 1959 .

[19]  Mark S. Granovetter.  The Strength of Weak Ties , 1973, American Journal of Sociology.

[20]  Kevin Crowston,et al.  Effective work practices for software engineering: free/libre open source software development , 2004, WISER '04.

[21]  Jonathan I. Maletic,et al.  Supporting source code difference analysis , 2004, 20th IEEE International Conference on Software Maintenance, 2004. Proceedings..

[22]  Bill Curtis,et al.  A field study of the software design process for large systems , 1988, CACM.

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

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

[25]  Ken Coar.  The Sun Never Sits on Distributed Development , 2003, ACM Queue.

[26]  Linda H. Rosenberg,et al.  Software Quality Metrics for Object-Oriented Environments , 2002 .

[27]  Michael L. Van de Vanter,et al.  The documentary structure of source code , 2002, Inf. Softw. Technol..

[28]  Karim R. Lakhani,et al.  Community, Joining, and Specialization in Open Source Software Innovation: A Case Study , 2003 .

[29]  Christopher R. Myers,et al.  Software systems as complex networks: structure, function, and evolvability of software collaboration graphs , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[30]  Thomas Hess,et al.  Supporting Global Software Development with Web 2.0 Technologies - Insights from and Empirical Study , 2008, AMCIS.

[31]  Kevin Crowston,et al.  Coordination of Free/Libre Open Source Software Development , 2005, ICIS.

[32]  Estelle Brodman,et al.  Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological Information Within the R&D Organization (Book Review) , 1978 .

[33]  Oliver Hein,et al.  The Impact of Fat Tailed Degree Distribution on Diffusion and Communication Processes , 2006 .

[34]  James Coplien,et al.  Social patterns in productive software development organizations , 1996, Ann. Softw. Eng..

[35]  Simon M. Kaplan,et al.  Scale-Free Nature of Java Software Package, Class and Method Collaboration Graphs , 2006 .

[36]  Guy Theraulaz,et al.  m s Self-Organization Patterns in Wasp and Open Source Communities , 2006 .

[37]  Jesús M. González-Barahona,et al.  Applying Social Network Analysis Techniques to Community-Driven Libre Software Projects , 2006, Int. J. Inf. Technol. Web Eng..