An Empirical Study on the Relation Between Programming Languages and the Emergence of Community Smells

To provide a measurable representation of social issues in software teams, the research community defined a set of anti-patterns that may lead to the emergence of both social and technical debt, i.e., “community smells”. Researchers have investigated community smells from different perspectives; in particular, they have analyzed how product-related aspects of software development, such as architecture and introducing a new language, could influence community smells. However, how technical project characteristics may be in relation to the emergence of community smells is still unknown. Different from those works, we aim to investigate how adopting specific programming languages might influence the socio-technical alignment and congruence of the development community, possibly inducing their overall ability to communicate and collaborate, leading to the emergence of social anti-patterns, i.e., community smells. We studied the relationship between the most used programming languages and the community smells in 100 open-source projects on G ITHub. Key results of the study show a low statistical correlation for specific community smells like Prima Donna Effects, Solution Defiance, and Organizational Skirmish, highlighting the fact that for some programming languages, its adoption could not be an indicator of the presence or absence of community smells.