Quantifying the /Social/ in Social Software Engineering

Abstract

Open source software repositories offer high resolution data about the collaboration of developers. These data are not only of interest for software engineering, they also benefit management and organization science. Thanks to the open source Python package git2net we are able to extract co-editing networks from git repositories. Combining network measures with fine grained analyses of code changes, we are able to quantify the productivity of developers, their coordination effort, and the resilience of OSS projects against the drop-out of core developers.

Short Biography

Frank Schweitzer has been Full Professor for Systems Design at ETH Zurich since 2004. He is also associated member of the Department of Physics at the ETH Zurich. The research of Frank Schweitzer focuses on applications of complex systems theory in the dynamics of social and economic organizations. He is interested in phenomena as diverse as user interaction in online social networks, collective decisions in animal groups, failure cascades and systemic risk in economic networks, and the rise and fall of collaborations in socio-technical systems. His methodological approach can be best described as data-driven modeling, i.e., it combines the insights from big data analysis with the power of agent-based computer simulations and the strength of rigorous mathematical models.

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