Approximate Model Checking of Stochastic COWS

Given the description of a model and a probabilistic formula, approximate model checking is a verification technique based on statistical reasoning that allows answering whether or not the model satisfies the formula. Only a subset of the properties that can be analyzed by exact model checking can be attacked by approximate methods. These latest methods, though, being based on simulation and sampling have the advantage of not requiring the generation of the complete state-space of the model. Here we describe an efficient tool for the approximate model checking of services written in a stochastic variant of COWS, a process calculus for the orchestration of services.

[1]  Håkan L. S. Younes,et al.  Verification and planning for stochastic processes with asynchronous events , 2004 .

[2]  Robert K. Brayton,et al.  Model-checking continuous-time Markov chains , 2000, TOCL.

[3]  Stefano Schivo.  Statistical Model Checking of Web Services , 2010 .

[4]  Joost-Pieter Katoen,et al.  Process algebra for performance evaluation , 2002, Theor. Comput. Sci..

[5]  Brian Campbell,et al.  Amortised Memory Analysis Using the Depth of Data Structures , 2009, ESOP.

[6]  Marta Z. Kwiatkowska,et al.  PRISM: probabilistic model checking for performance and reliability analysis , 2009, PERV.

[7]  M. Siegle,et al.  Multi Terminal Binary Decision Diagrams to Represent and Analyse Continuous Time Markov Chains , 1999 .

[8]  W. Hoeffding.  Probability Inequalities for sums of Bounded Random Variables , 1963 .

[9]  Thomas Hérault,et al.  APMC 3.0: Approximate Verification of Discrete and Continuous Time Markov Chains , 2006, Third International Conference on the Quantitative Evaluation of Systems - (QEST'06).

[10]  Paola Quaglia,et al.  A Tool for Checking Probabilistic Properties of COWS Services , 2010, TGC.

[11]  Francesco Tiezzi,et al.  A Calculus for Orchestration of Web Services , 2007, ESOP.

[12]  Matthias Kuntz,et al.  Symbolic semantics and verification of stochastic process algebras , 2006 .

[13]  Alan Bundy,et al.  Constructing Induction Rules for Deductive Synthesis Proofs , 2006, CLASE.

[14]  Priya Narasimhan,et al.  Service-Oriented Computing - ICSOC 2007, Fifth International Conference, Vienna, Austria, September 17-20, 2007, Proceedings , 2007, ICSOC.

[15]  Thomas Hérault,et al.  Approximate Probabilistic Model Checking , 2004, VMCAI.

[16]  Jane Hillston,et al.  A compositional approach to performance modelling , 1996 .

[17]  A. Wald.  Sequential Tests of Statistical Hypotheses , 1945 .

[18]  Masahiro Fujita,et al.  Multi-Terminal Binary Decision Diagrams: An Efficient Data Structure for Matrix Representation , 1997, Formal Methods Syst. Des..

[19]  Paola Quaglia,et al.  Stochastic COWS , 2007, ICSOC.

[20]  Kousha Etessami,et al.  Analysis of Recursive Game Graphs Using Data Flow Equations , 2004, VMCAI.

[21]  Diego Latella,et al.  MarCaSPiS: a Markovian Extension of a Calculus for Services , 2009, SOS@ICALP.