Abstract
Modern automotive electric/electronic (E/E) architectures are growing to the point where architects can no longer manually predict the effects of their design decisions. Thus, in addition to applying an architecture reference model to decompose their architectures, they also require tools for synthesizing and evaluating candidate architectures during the design process. Clafer is a modeling language, which has been used to model variable multi-layer, multi-perspective automotive system architectures according to an architecture reference model. Clafer tools allow architects to synthesize optimal candidates and evaluate effects of their design decisions. However, since Clafer is a general-purpose structural modeling language, it does not help the architects in building models conforming to the given architecture reference model. In this paper, we present an E/E architecture domain-specific language (DSL) built on top of Clafer, which embodies the reference model and which guides the architects in correctly applying it. We evaluate the DSL and its implementation by modeling two existing automotive systems, which were originally modeled in plain Clafer. The evaluation showed that by using the DSL, an evaluator obtained correct models by construction because the DSL helped prevent typical errors that are easy to make in plain Clafer. The evaluator was also able to synthesize and evaluate candidate architectures as with plain Clafer.
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Notes
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Throughout this paper if the word Clafer begins with an uppercase letter it refers to the language while a lowercase one refers to the language construct.
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Khalilov, E., Ross, J., Antkiewicz, M., Völter, M., Czarnecki, K. (2016). Modeling and Optimizing Automotive Electric/Electronic (E/E) Architectures: Towards Making Clafer Accessible to Practitioners. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation: Discussion, Dissemination, Applications. ISoLA 2016. Lecture Notes in Computer Science(), vol 9953. Springer, Cham. https://doi.org/10.1007/978-3-319-47169-3_37
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