Information about the evolution of a software architecture can be found in the source basis of a project and in the release history data such as modification and problem reports. Existing approaches deal with these two data sources separately and do not exploit the integration of their analyses. In this paper, we present an architecture analysis approach that provides an integration of both kinds of evolution data. The analysis applies fact extraction and generates specific directed attributed graphs; nodes represent source code entities and edges represent relationships such as accesses, includes, inherits, invokes, and coupling between certain architectural elements. The integration of data is then performed on a meta-model level to enable the generation of architectural views using binary relational algebra. These integrated architectural views show intended and unintended couplings between architectural elements, hence pointing software engineers to locations in the system that may be critical for on-going and future maintenance activities. We demonstrate our analysis approach using a large open source software system.