Extending the Potts and Bruns model for recording design rationale
ICSE '91 Proceedings of the 13th international conference on Software engineering
A generic model for reflective design
ACM Transactions on Software Engineering and Methodology (TOSEM)
IWSSD '96 Proceedings of the 8th International Workshop on Software Specification and Design
Architecture Decisions: Demystifying Architecture
IEEE Software
Software Architecture as a Set of Architectural Design Decisions
WICSA '05 Proceedings of the 5th Working IEEE/IFIP Conference on Software Architecture
A survey of architecture design rationale
Journal of Systems and Software
A rationale-based architecture model for design traceability and reasoning
Journal of Systems and Software
Enterprise Architecture: Creating Value by Informed Governance
Enterprise Architecture: Creating Value by Informed Governance
Enterprise Architecture at Work: Modelling, Communication and Analysis
Enterprise Architecture at Work: Modelling, Communication and Analysis
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ArchiMate is a Domain Specific Language (DSL) to model an enterprise from a holistic perspective, showing not only the IT infrastructure of an organization, but also how this IT infrastructure supports business processes and contributes to the realization of products and (commercial) services. Yet, ArchiMate lacks the capability to capture the design decisions behind the models. Capturing such decisions is important to improve the design teaching and communication after the design process. This is what we refer to as EA Anamnesis. People who can benefit from EA Anamnesis are e.g. persons that are foreign to a given architecture, such as external Enterprise architects. In this paper, we introduce an approach to capture design decisions. For the moment we target our approach primarily on capturing design decisions in the context of ArchiMate models. Specifically, we (1) introduce a metamodel for capturing architectural design decisions. This metamodel is grounded in DSLs for capturing rationales in software engineering. (2) Finally, we provide a fictitious use case scenario for the insurance industry to illustrate the use of our approach.