SEJul 21, 2017

Mastering Heterogeneous Behavioural Models

arXiv:1707.06858v13 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of managing heterogeneity in system modeling for engineers and researchers, though it appears incremental as it builds on existing compatibility assumptions.

The paper tackles the problem of composing heterogeneous behavioral models in complex systems by proposing an algebra and structure morphisms to ensure safe interactions, enabling incremental construction and analysis.

Heterogeneity is one important feature of complex systems, leading to the complexity of their construction and analysis. Moving the heterogeneity at model level helps in mastering the difficulty of composing heterogeneous models which constitute a large system. We propose a method made of an algebra and structure morphisms to deal with the interaction of behavioural models, provided that they are compatible. We prove that heterogeneous models can interact in a safe way, and therefore complex heterogeneous systems can be built and analysed incrementally. The Uppaal tool is targeted for experimentations.

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