As software evolves, maintenance practices require a process of accommodating changing requirements while minimizing the cost of implementing those changes. Over time, incompatibilities between design assumptions and the operational environment become more pronounced, requiring some regions of the implementation to require repeated modification. These regions are considered to be "unstable", and may benefit from targeted restructuring efforts as a means of realigning these assumptions and the environment. An analysis of these regions that identifies and classifies these instabilities can be used to prioritize and direct structural maintenance efforts. To this end, we present an identification approach that augments static dependence graphs with data retrieved from configuration management (CM) systems. This approach avoids the assumption that artifacts changing within the same CM transaction are related, without requiring sophisticated change management data. We also describe our work-to-date in validating the underlying assumptions and identifying instabilities.