In order to lower the risk, reengineering projects aim at high reuse rates. Therefore, tasks like architectural restructuring have to be performed in a way that developed new system architectures allow reuse of all valuable legacy systems' parts with minimal changes. During architectural restructuring there are two major types of modification: detection of architecture disproportions and their refactoring and detection of redundancies and their fusion. In this paper we introduce a method for

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... lying domain knowledge for supporting these restructuring steps. The method operates on feature models. Words and terms of features and of architectural documents are analyzed by cluster analysis, information retrieval and metrics techniques. In this way, the method joins the approaches of feature analysis and of enhancing reengineering with domain knowledge by applying feature models for structuring the domain knowledge. The method results in clues and hints for the development of a new architecture. It provides an effective addition to the conventional software architecture design methods. The method was developed and applied in an industrial reengineering project within image processing domain. It has been proved to be applicable to large and complex systems even in case of heavy monolithic parts. We use examples from this project to illustrate the method.