Evolutionary information about software systems has proven to be a good resource to complement existing reverse engineering approaches, because it helps in giving a historical perspective of the system to be reverse engineered. Moreover, it provides additional types of information that are not present when only one version of a system is considered. Logical coupling, the implicit dependency between artifacts which changed together, is one example of such information. However, the recurrent problem is that such information comes in large amounts and must be processed to be useful for the reverse engineering of a system.

In this paper we propose an approach to use logical coupling information at different levels of abstraction to detect areas in the system which may lead to maintenance problems. They represent a good starting point to decrease the coupling in the system. Our approach uses an interactive visualization technique called the Evolution Radar, which can effectively break down the amount and complexity of the logical coupling information. We present our technique in detail and apply it on a large open-source software system.