More than 90% of the cost of software is due to maintenance and evolution. Understanding the evolution of large software systems is a complex problem, which requires the use of various techniques and the support of tools. Several software evolution approaches put the emphasis on structural entities such as packages, classes and structural relationships. However, software evolution is not only about the history of software artifacts, but it also includes other types of data such as problem reports, mailing list archives etc. We propose an approach which focuses on historical dependencies and defects. We claim that they play an important role in software evolution and they are complementary to techniques based on structural information. We use historical dependencies and defect information to learn about a software system and detect potential problems in the source code. Moreover, based on design flaws detected in the source code, we predict the location of future bugs to focus mainten...