Splicing Community Patterns and Smells: A Preliminary Study

Software engineering projects are now more than ever a community effort. In the recent past, researchers have shown that their success may not only depend on source code quality, but also on other aspects like the balance of distance, culture, global engineering practices, and more. In such a scenario, understanding the characteristics of the community around a project and foresee possible problems may be the key to develop successful systems. In this paper,we focus on this research problem and propose an exploratorystudy on the relation between community patterns, i.e., recurrentmixes of organizational or social structure types, and smells, i.e.,sub-optimal patterns across the organizational structure of a softwaredevelopment community that may be precursors of some sortof social debt. We exploit association rule mining to discover frequentrelations between them. Our findings show that differentorganizational patterns are connected to different forms of sociotechnicalproblems, possibly suggesting that practitioners shouldput in place specific preventive actions aimed at avoiding the emergenceof community smells depending on the organization of theproject.