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Electrical Engineering and Computer Science

Model-Integrated Computing Research


Information processing is increasingly becoming an integral part of physical systems. It dramatically increases the potential interactions among physical components and processes, generates complex dynamics, and establishes component interdependencies unknown in previous-generation systems. The tight integration of "physical" and "information" processes creates tremendous challenges for the software technology. First of all the "conceptual construct" of the software is inextricably combined with the conceptual construct of its "external environment"; that is, with the structure of physical processes. Consequently, the software cannot be static, it must change, evolving together with its embedding environment. Another well-known difficulty in the design and implementation of embedded information systems is that software is becoming a component of a physical system. The overall system behavior can only be understood if information, material and energy transfer processes are modeled and analyzed together. This means that software artifacts need to be modeled "in their context", using a modeling language - or modeling paradigm - that is meaningful for the design, analysis and operation of the whole system. An additional challenge that must be answered is criticality. Software directly impacts the operation of physical processes and failure may cause unacceptable social or economic damage. Thus the software technology must offer methods and tools for verifying and maintaining dependability requirements.

Model-Integrated Computing (MIC) addresses these problems by providing rich, domain-specific modeling environments including model analysis and model-based program synthesis tools. This technology is used to create and evolve integrated, multiple-aspect models using concepts, relations, and model composition principles routinely used in the specific field, to facilitate systems/software engineering analysis of the models, and to automatically synthesize applications from the models.


  • Modeling Languages
  • Embedded Systems Applications
  • Semantic Integration of Design Tools
  • Verification of Complex Finite-State Systems


Research Centers and Laboratories