Exploring software variance with hypermodelling – an exemplary approach

Abstract

Framework manufacturers face the challenge to determine which parts of frameworks are used and varied. Application developers want to know on which framework elements their application is depending. Currently, programs need to be parsed to extract information about framework usage what consumes time and effort and makes information mining inflexible. Hypermodelling utilizes Data Warehouse technologies for source code investigations to overcome the current limitations. In this paper, we demonstrate that Hypermodelling is suitable to explore software variance. We present reports based on real application data of one project example to reveal multiple facts about the software variance. We show visualizations at different granularity levels. This supports our theory that Hypermodelling can be used to explore software variance in an easy way.