Mining Problem-solving Behaviour from Open-Source Respositories

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Open Source systems such as Linux and Mozilla are both innovative and popular. They are built by an informal group of volunteers, working in a distributed, asynchronous manner. Communication and coordination are mediated by emails and shared repositories (containing manuals, design documents, source code and bug reports). This repository constitutes an extensive on-line record of user feedback, artifact evolution and task-related problem-solving behaviors. This data is publicly available, and is amenable to modern data mining techniques, as well as automated program analysis algorithms. Our goal is to integrate these automated analyses with social science methods to study the intrinsic relationship between community behavior and software engineering outcomes in large-scale open source projects, with view to improving software engineering practice. We have assembled an inter-disciplinary research team consisting of a software engineer, a social scientist, and a database researcher. Software systems have an enormous impact on the economy and on society; an improved understanding of the social processes underlying software development could well lead to faster development of cheaper, better software systems. Our interdisciplinary collaboration builds on existing work by explicitly connecting software engineering imperatives to the techniques of social science; thus we hope to evaluate the relevance of folklore principles such as "Conway's Law," that claims a relationship between artifact structure and community structure. Finally this collaboration will help us formulate new, much-needed interdisciplinary pedagogy to train both undergraduate and graduate software engineers in the social aspects of software development: team-building, work allocation, coordination, project management, and process improvement.