A Collaboration Model for Community-Based Software Development with Social Machines

Abstract: Crowdsourcing is generally used for tasks with minimal coordination, providing limited support for dynamic reconfiguration. Modern systems, exemplified by social machines, are subject to continual flux in both the client and development communities and their needs. To support crowd sourcing of open-ended development, systems must dynamically integrate human creativity with machine support. While workflows can be used to handle structured, predictable processes, they are less suitable for social machine development and its attendant uncertainty. We present models and techniques for coordination of human workers in crowd sourced software development environments. We combine the Social Compute Unit—a model of ad-hoc human worker teams—with versatile coordination protocols expressed in the Lightweight Social Calculus. This allows us to combine coordination and quality constraints with dynamic assessments of end-user desires, dynamically discovering and applying development protocols.

Citation: Dave Murray-Rust, Ognjen Scekic, Hong-Linh Truong, Dave Robertson and Schahram Dustdar. A Collaboration Model for Community-Based Software Development with Social Machines. 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 22-25 Oct, Miami, FL, USA, 2014.

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About P. Andreadis

Pre-Doctoral Research Assistant in AI and Social Computation @ University of Edinburgh.

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