A multi-paradigm modeling and simulation methodology: formalisms and languages

1 Abstract Recently, the interest in Computer Aided Engineering of complex systems has increased 1]. This increase is mainly due to the growing complexity of systems under study. This article focuses on systems characterised, not so much by a large number of components, but rather by the diversity of the components. A simpliied example of an environmental system is presented. For the analysis and design of such complex systems, it is no longer suucient to study the diverse components separately, using the speciic formalisms these components were modelled in. Rather, it becomes necessary to answer questions about properties (most notably behaviour) of the whole system. This article discusses in an informal manner, the concept of \formalism" which is the key to expressing semantics of models. Those models can be represented using diierent modelling languages. It is shown how diierent modelling languages are related to one another, enabling meaningful model exchange and re-use. Some particular model representations are suited for use by a \solver", allowing the model to be simulated. The general architecture of simulators is presented. In certain cases, it is possible to describe a mathematical relationship between diierent formalisms. This mapping may be implemented as a translator between modelling languages. Transformation between formalism has diierent uses. Firstly, certain questions about a system can only be answered in certain formalisms, necessitating model transformation to the appropriate formalism. Secondly, to elicit the meaning of a coupled model consisting of sub-models in diierent formalisms, transformation of these sub-models to a common formalism is appropriate. This transformation process will be demonstrated. 2 Introduction The analysis, design and control of complex systems (hardware, software and hybrid) involves the manipulation of diierent abstract representations or \models" of these systems. Typical abstractions or formalisms used in physical systems modelling are bond graphs, Petri-nets, diierential equations and queueing networks. In software systems, abstractions include nite state automata and entity relationship diagrams. The representation and manipulation of system models using diierent formalisms has been a task allotted to the experienced mod-eller, who traverses the modelling life-cycle, from goals, through multiple abstract models, into a concrete implementation. This process has hitherto remained internalised (i.e., the modeller's experience), limiting the chances of its successful automation. Due to the continuing integration of hardware and software, there is a growing need for integrated modelling support. It is suggested that a rigorous multi-paradigm modelling methodology will provide a backbone for complex decision-making. One …