NODE MIXING AND GROUP STRUCTURE OF COMPLEX SOFTWARE NETWORKS

Lovro Šubelj (), Slavko Žitnik (), Neli Blagus () and Marko Bajec ()
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Lovro Šubelj: Faculty of Computer and Information Science, University of Ljubljana, Večna Pot 113, SI-1000, Ljubljana, Slovenia
Slavko Žitnik: Faculty of Computer and Information Science, University of Ljubljana, Večna Pot 113, SI-1000, Ljubljana, Slovenia
Neli Blagus: Faculty of Computer and Information Science, University of Ljubljana, Večna Pot 113, SI-1000, Ljubljana, Slovenia
Marko Bajec: Faculty of Computer and Information Science, University of Ljubljana, Večna Pot 113, SI-1000, Ljubljana, Slovenia

Advances in Complex Systems (ACS), 2014, vol. 17, issue 07n08, 1-26

Abstract: Large software projects are among most sophisticated human-made systems consisting of a network of interdependent parts. Past studies of software systems from the perspective of complex networks have already led to notable discoveries with different applications. Nevertheless, our comprehension of the structure of software networks remains to be only partial. Here we investigate correlations or mixing between linked nodes and show that software networks reveal dichotomous node degree mixing similar to that recently observed in biological networks. We further show that software networks also reveal characteristic clustering profiles and mixing. Hence, node mixing in software networks significantly differs from that in, e.g., the Internet or social networks. We explain the observed mixing through the presence of groups of nodes with common linking pattern. More precisely, besides densely linked groups known as communities, software networks also consist of disconnected groups denoted modules, core/periphery structures and other. Moreover, groups coincide with the intrinsic properties of the underlying software projects, which promotes practical applications in software engineering.

Keywords: Software networks; node mixing; node groups; software engineering (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219525914500222

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