Much attention is paid nowadays to software architecture of a system as a set of design decisions providing the rationale for the system design. To document and share proven architectural design decisions, decisions made in concrete development projects are mined and distilled into reusable architectural decision models (a.k.a. guidance models). The available distillation approaches, however, remain ad hoc and biased towards the personal experience of few expert architects. Relationships between distilled decisions are not systematically explored. We propose an approach for distilling reusable architectural design decisions with emphasis on their relationships. Architectural knowledge artifacts (e.g., architecture documentation, interviews) are systematically coded for the occurrence of architectural design decisions and their details. Co-occurrences of coded design decisions are then processed for different relationship types using an established data-mining technique: frequent item-sets. The distilled relationships enter the construction of a reusable architectural decision model and contribute to organizing the design space based on empirical data (i.e., frequency patterns of co-occurrences). We report on distilling design-decision relationships from decision data collected during a three-year project on language architectures of 80 UML-based domain-specific modeling languages.

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