Data-driven Mobile App Design.

ABSTRACTDesign is becoming a key differentiating factor for successful apps in today's crowded app marketplaces. This thesis describes how data-driven approaches can enable useful tools for mobile app design. It presents interaction mining -- capturing both static (UI layouts, visual details) and dynamic (user flows, motion details) components of an app's design. It develops two approaches for interaction mining existing Android apps and presents three applications enabled by the resultant data: a search engine for user flows, lightweight usability testing at scale, and automated generation of mobile UIs.