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An Introduction to Multiformalism Modeling
Abstract
The fundamental need for models in every field of design stems from the absolute and essential necessity for complexity domination. The prediction and verification competence is a must-have ability to allow an efficient and effective design cycle, as much as the complexity of the requirements, in specification, extension or criticalness of the design object, grows. Researchers and practitioners have developed different modeling languages to suit the needs of special classes of problems, such as general formalism like Fault Trees for dependability and availability models, several Petri Nets variants for performance and correctness evaluation, or dedicated modeling languages that map model elements onto domain entities. Richness and variety of formalisms, each of which tailored on a specific problem, empowers the modeling process, but also results in the explosion of many different submodels when coping with a complex and articulated system. These models are logically correlated and are used to take local decisions about single aspects of the overall problem. In practice they might not be aligned to each other and the mutual influences connecting them could be lost, compromising the general results. Multiformalism is an approach to modeling that aims to enable modelers to exploit together different formalisms for different aspects of the same system, while keeping the coherence and the mutual influences of the different parts of the overall model. Different concepts and interpretation of multiformalism modeling (and related problems, such multiparadigm and multisolution) have been experimented and are documented in literature. In this chapter, the main ideas and results in the field are introduced, together with an analysis and comparison.
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