Extended Assortitivity and the Structure in the Open Source Development Community

Open source software development represents the work of hundreds of thousands (perhaps millions) of developers around the world and is a critical component of many widely-used software products. Much of this development is self-organizing, taking place outside the structures of specific organizations. In this regard, open-source development communities are similar to academic research communities, which are also self-organizing and trans-institutional in nature. The structure of academic research communities has been characterized by the use of Bibliometrics techniques, which provide a quantitative basis for the self-organizing networks of academic artifacts (publications). In this paper, we introduce ‘Developmetrics,’ the application of Bibliometrics techniques to similarly characterize the artifacts produced by open source development (software). Similar cross-over analysis has been done before in the study of other self-organizing networks, such as the Internet. We use a standard Bibliometrics visualization technique to guide our discussion and we introduce extensions to concepts of network assortativity, node afference and node efference to accommodate network meta-data. With the help of these tools, we investigate issues related to community formation and the product development life-cycle. Through visualizations and measurement, we show that the strongest organizing factor in the open source community is the choice of programming language. This paper describes how we reached this (and other insights) and discusses the implications these results may have on open source software development. We also discuss future questions and directions for Developmetrics analysis.