Problem Definition

The systems we analyse, design, and develop today are characterized by an ever growing com-plexity. Modelling and Simulation (M&S) become increasingly important enablers in the de-velopment of such systems. Building models, often abstractions, of the system, that can be checked, simulated, and optimized before any realization of the system is made allows for a tremendous decrease in cost, while increasing the overall quality of the delivered system. Fur-thermore, it is often also possible to synthesize parts of the system from these models. The M&S approach can only be successful if the modeller (often a domain expert, such as an automotive engineer) has access to advanced tools which enable the creation of models and provide the necessary framework for performing simulation and deployment of models onto hardware. Core activities include the initialization of the system with a set of values, results collection (after simulation has been performed), and acceptance or rejection of simulation re-sults according to predefined simulation objectives. This framework, called the Experimental Frame (EF), was introduced by Zeigler [1]. Traore ́ and Muzy [2] use EFs to make a clear distinction between what is inherent to the model, which is an abstraction of a (sub)system to be analysed, and its context, which contains all information needed to run the simulation