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During software evolution, adaptive, and corrective maintenance are common reasons for changes. Often such changes cluster around key components. It is therefore important to analyze the frequency of changes to individual classes, but, more importantly, to also identify and show related changes in multiple classes. Frequent changes in clusters of classes may be due to their importance, due to the underlying architecture or due to chronic problems. Knowing where those change-prone clusters are can help focus attention, identify targets for re-engineering and thus provide product-based information to steer maintenance processes. This paper describes a method to identify and visualize classes and class interactions that are the most change-prone. The method was applied to a commercial embedded, real-time software system. It is object-oriented software that was developed using design patterns.