From Model Checking to Model Measuring

  • Thomas A. Henzinger
  • Jan Otop
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8052)


We define the model-measuring problem: given a model M and specification ϕ, what is the maximal distance ρ such that all models M′ within distance ρ from M satisfy (or violate) ϕ. The model measuring problem presupposes a distance function on models. We concentrate on automatic distance functions, which are defined by weighted automata. The model-measuring problem subsumes several generalizations of the classical model-checking problem, in particular, quantitative model-checking problems that measure the degree of satisfaction of a specification, and robustness problems that measure how much a model can be perturbed without violating the specification. We show that for automatic distance functions, and ω-regular linear-time and branching-time specifications, the model-measuring problem can be solved. We use automata-theoretic model-checking methods for model measuring, replacing the emptiness question for standard word and tree automata by the optimal-weight question for the weighted versions of these automata. We consider weighted automata that accumulate weights by maximizing, summing, discounting, and limit averaging. We give several examples of using the model-measuring problem to compute various notions of robustness and quantitative satisfaction for temporal specifications.


Similarity Measure Model Check Transition System Weighting Scheme Linear Temporal Logic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas A. Henzinger
    • 1
  • Jan Otop
    • 1
  1. 1.ISTAustria

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