Open Source Software Development (OSSD) often suffers from conflicting views and actions due to the perceived flat and open ecology of an open source community. This often manifests itself as a lack of codified knowledge that is easily accessible for community members. How decisions are made and expectations of a software system are often described in detail through the many forms of social communications that take place within a community. These social interactions form norms which are influential in dictating what behaviors are expected in a community and of the system. In this paper, we provide a tool which mines these social interactions (in the form of bug reports) and extract norms of the system, externalizing this information into a codified form that allows others within the community to be aware of without having witnessed the social interactions.

Social norms facilitate coordination and cooperation among individuals, thus enable smoother functioning of social groups such as the highly distributed and diverse open source software development (OSSD) communities. In these communities, norms are mostly implicit and hidden in huge records of human-interaction information such as emails, discussions threads, bug reports, commit messages and even source code. This paper aims to introduce a new line of research on extracting social norms from the rich data available in software repositories. Initial results include a study of coding convention violations in JEdit, Argo UML and Glassfish projects. It also presents a new life-cycle model for norms in OSSD communities and demonstrates how a number of norms extracted from the Python development community follow this life-cycle model.