Saturation unbound

  • Authors:
  • Gianfranco Ciardo;Robert Marmorstein;Radu Siminiceanu

  • Affiliations:
  • College of William and Mary, Williamsburg, Virginia;College of William and Mary, Williamsburg, Virginia;College of William and Mary, Williamsburg, Virginia

  • Venue:
  • TACAS'03 Proceedings of the 9th international conference on Tools and algorithms for the construction and analysis of systems
  • Year:
  • 2003

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Abstract

In previous work, we proposed a "saturation" algorithm for symbolic state-space generation characterized by the use of multivalued decision diagrams, boolean Kronecker operators, event locality, and a special iteration strategy. This approach outperforms traditional BDD-based techniques by several orders of magnitude in both space and time but, like them, assumes a priori knowledge of each submodel's state space. We introduce a new algorithm that merges explicit local state-space discovery with symbolic global state-space generation. This relieves the modeler from worrying about the behavior of submodels in isolation.