The analysis of the evolution of software [16] has two main goals, namely to infer causes of its current problems, and to predict its future development. Many approaches based on evolutionary information demonstrated that not only can such information be used to predict the future evolution [18], but it can also point out potential problems in the system [12]. Understanding the evolution of large software systems is a complex problem for several reasons: huge amounts of information have to be considered and historical data has to be analyzed to understand the phenomena of evolution and to infer causes of problems. The evolution of a software system is not only the collection of all the versions of its components: developing software is a human activity, and the evolution of a software system also includes the activities performed by developers, testers, users, etc. during the entire history of the system. This additional information comes from various sources such as comments committed by developers during the implementation, problem reports delivered by users and stored in bug tracking systems, mailing list archives, etc. Several software evolution analysis techniques have been proposed which either focus on the source code and its evolution, without exploiting other data sources such as problem reports, or they use additional information (e.g., e-mail archives), without a direct link to the source code.