Towards automated analysis of model-driven artifacts in industry

\u3cp\u3eDeveloping complex (sub)systems is a multi-disciplinary activity resulting in several, complementary models, possibly on different abstraction levels. The relations between all these models are usually loosely defined in terms of informal documents. It is not uncommon that only till the moment of integration at implementation level, shortcomings or misunderstanding between the different disciplines is revealed. In order to keep models consistent and to reason about multiple models, the relations between models have to be formalized. MultiDisciplinary System Engineering (MDSE) ecosystems provide a means for this. These ecosystems formalize the domain of interest using Domain Specific Languages (DSLs), and formalize the relations between models by means of automated model transformations. This enables consistency checking between domain and aspect models and facilitates multi-disciplinary analysis of the single (sub)system at hand. MDSE ecosystems provide the means to analyze a single (sub)system model. A set of models of different (sub)systems can be analyzed to derive best modeling practices and modeling patterns, and to measure whether a MDSE ecosystem fulfills its needs. The MDSE ecosystem itself can be instrumented to analyze how the MDSE ecosystem is used in practice. The evolution of models, DSLs and complete MDSE ecosystems is studied to identify and develop means that support evolution at minimal costs while maintaining high quality. In this paper, we present the anatomy of MDSE ecosystems with industrial examples, the ongoing work to enable the various types of analysis, each with their dedicated purpose. We conclude with a number of future research directions.\u3c/p\u3

Towards automated analysis of model-driven artifacts in industry

Developing complex (sub)systems is a multi-disciplinary activity resulting in several, complementary models, possibly on different abstraction levels. The relations between all these models are usually loosely defined in terms of informal documents. It is not uncommon that only till the moment of integration at implementation level, shortcomings or misunderstanding between the different disciplines is revealed. In order to keep models consistent and to reason about multiple models, the relations between models have to be formalized. MultiDisciplinary System Engineering (MDSE) ecosystems provide a means for this. These ecosystems formalize the domain of interest using Domain Specific Languages (DSLs), and formalize the relations between models by means of automated model transformations. This enables consistency checking between domain and aspect models and facilitates multi-disciplinary analysis of the single (sub)system at hand. MDSE ecosystems provide the means to analyze a single (sub)system model. A set of models of different (sub)systems can be analyzed to derive best modeling practices and modeling patterns, and to measure whether a MDSE ecosystem fulfills its needs. The MDSE ecosystem itself can be instrumented to analyze how the MDSE ecosystem is used in practice. The evolution of models, DSLs and complete MDSE ecosystems is studied to identify and develop means that support evolution at minimal costs while maintaining high quality. In this paper, we present the anatomy of MDSE ecosystems with industrial examples, the ongoing work to enable the various types of analysis, each with their dedicated purpose. We conclude with a number of future research directions