Model-based tool-chain infrastructure for automated analysis of embedded systems

  • Authors:
  • Hang Su;Graham Hemingway;Kai Chen;T. John Koo

  • Affiliations:
  • Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN;Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN;Motorola Labs, Motorola Inc., Schaumburg, IL;Departments of Electronics Engineering and Computer Science, Shantou University, Shantou, Guangdong, China

  • Venue:
  • ATVA'06 Proceedings of the 4th international conference on Automated Technology for Verification and Analysis
  • Year:
  • 2006

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Abstract

In many safety-critical applications of embedded systems, the system dynamics exhibits hybrid behaviors. To enable automatic analysis of these embedded systems, many analysis tools have been developed based on hybrid automata model. These tools are constructed by their own domain-specific modeling languages (DSMLs) but they are different in various aspects. To enable meaningful semantic interpretation of DSMLs, we propose an infrastructure for semantic anchoring that facilitates the transformational specification of DSML semantics. In the semantic anchoring infrastructure, the semantics of a DSML can be anchored to a well-defined semantic unit, which captures the operational semantics of hybrid automaton, via model transformation. The Abstract State Machine (ASM) is used as the underlying formal framework for the semantic unit. The semantics of a DSML is defined by specifying the transformation between the abstract syntax metamodel of the DSML and that of the semantic unit. The infrastructure can also enable model exchange among DSMLs while referring to the common semantic unit. Hence, hybrid automata based DSMLs can be integrated to form a meaningful tool chain by deploying this proposed infrastructure. In this paper, we demonstrate how effective the tool-chain infrastructure is by considering a practical case study involving the hybrid automata DSMLs, HyVisual and ReachLab.