Component Clustering Based on Maximal Association**This work was funded by IBM Canada Ltd. Laboratory - Center for Advanced Studies (Toronto) and the National Research Council of Canada.

In this paper, we present a supervised clustering framework for recovering the architecture of a software system. The technique measures the association between the system components (such as files) in terms of data and control flow dependencies among the groups of highly related entities that are scattered throughout the components. The application of data mining techniques allows to extract the maximum association among the groups of …