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Node Mixing And Group Structure Of Complex Software Networks

Author

Listed:
  • 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)

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.

Suggested Citation

  • Lovro Šubelj & Slavko Žitnik & Neli Blagus & Marko Bajec, 2014. "Node Mixing And Group Structure Of Complex Software Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 17(07n08), pages 1-26.
  • Handle: RePEc:wsi:acsxxx:v:17:y:2014:i:07n08:n:s0219525914500222
    DOI: 10.1142/S0219525914500222
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    Cited by:

    1. Blagus, Neli & Šubelj, Lovro & Weiss, Gregor & Bajec, Marko, 2015. "Sampling promotes community structure in social and information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 206-215.

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