Visual data mining in software archives

Software archives contain historical information about the development process of a software system. Using data mining techniques rules can be extracted from these archives. In this paper we discuss how standard visualization techniques can be applied to interactively explore these rules. To this end we extended the standard visualization techniques for association rules and sequence rules to also show the hierarchical order of items. Clusters and outliers in the resulting visualizations provide interesting insights into the relation between the temporal development of a system and its static structure. As an example we look at the large software archive of the MOZILLA open source project. Finally we discuss what kind of regularities and anomalies we found and how these can then be leveraged to support software engineers.

• Type: Conference
• Year: 2005
• Where: SOFTVIS
• Authors: Michael Burch, Stephan Diehl, Peter Weißgerber
• Keywords: Mining Techniques Rules, SOFTVIS 2005, Software Archive, Standard Visualization Techniques