Software Clustering Based on Dynamic Dependencies
Chenchen Xiao, Vassilios Tzerpos · 2005
The reverse engineering literature contains many software clustering approaches that attempt to cluster large software systems based on the static dependencies between software artifacts. However, the usefulness of clustering based on dynamic dependencies has not been investigated. It is possible that dynamic clusterings can provide a fresh outlook on the structure of a large software system. In this paper, we present an approach for the evaluation of dynamic clusterings. We apply this approach to a large open source software system, and present experimental results that suggest that dynamic clusterings have considerable merit.