Software archives are a rich source of information about the development process of a software system. Using data mining techniques rules can be extracted from these archives. Rules can either be association rules which means that software items have been changed together with a certain probability or sequence rules which means items have been changed one after the other. The change frequency (support) as well as the change probability (confidence) of a given rule are both metrics used for visualizing the strength of a rule. EPOSee is a tool designed to interactively explore these kinds of rules. To this end we extended standard visualization techniques for association 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.
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