Authors: Diana El Rabih, Gael Gorgo, Nihal Pekergin, Jean-Marc Vincent
Addresses: LACL, University of Paris-Est Creteil Val de Marne, 61 Avenue General de Gaulle, 94010, Creteil, France. ' LIG, University of Grenoble, 51, Avenue Jean Kuntzmann, 38330 Montbonnot, France. ' LACL, University of Paris-Est Creteil-Val de Marne, 61 Avenue General de Gaulle, 94010, Creteil, France. ' LIG, University of Grenoble, 51, Avenue Jean Kuntzmann, 38330 Montbonnot, France
Abstract: Model checking of probabilistic models can be done either by numerical analysis or by simulation and statistical methods. In this paper, we compare the efficiency and the scalability of these approaches when they are applied to the verification of steady state properties of very large models. We provide an experimental comparison study between the statistical model checking using perfect sampling, the numerical method implemented in model checker PRISM and the statistical model checking implemented in model checker MRMC for the verification of CSL steady state properties. We show that the statistical approach using perfect sampling is generally more efficient than the two other approaches and it allows us to consider very large models and to verify rare event properties efficiently.
Keywords: model checking; probabilistic verification; continuous stochastic logic; CSL; dependability verification; perfect simulation; probabilistic modelling; very large models; steady state; rare event properties.
International Journal of Critical Computer-Based Systems, 2011 Vol.2 No.3/4, pp.309 - 331
Available online: 04 Sep 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article