Node mixing and group structure of complex software networks
This work provides insights into the structural organization of large software projects, which is incremental as it builds on prior complex network studies to better understand software engineering systems.
The study investigated node mixing and group structures in complex software networks, revealing dichotomous degree mixing similar to biological networks and distinct clustering profiles compared to other networks like the Internet or social networks. The findings show that these structures correlate with intrinsic software project properties, enabling practical applications in software engineering.
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. We here 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.