| Abstrakt: |
Assessing the collaboration among developers is important to understand different aspects of software lifecycle including code smell intensity, bug fixes, and software quality. This kind of collaboration can be obtained from social networks, which represent interactions between individuals in different contexts. In this paper, we model GitHub developers' collaborations in a heterogeneous network by considering three aspects: social collaboration, collaboration time in a repository and technical features. Then, we explore the GitHub network from different perspectives: size, relevance, and potential applications. The results show the considered metrics are not correlated, bringing new information about the collaborations. We also show that such information is useful for social developer ranking, an actual task which is often part of different applications, such as team formation, community detection and pair programming. Finally, as software quality is intrinsic to the people who code it, our methodology and analyses represent initial steps towards people-centered software quality analysis, as further discussed throughout this article. [ABSTRACT FROM AUTHOR] |
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