Symbolic Performance and Dependability Evaluation with the Tool CASPA

This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams (MTBDD) to represent the labelled continuous time Markov chain (CTMC) underlying a given process algebraic specification. All phases of modelling, from model construction to numerical analysis and measure computation, are based entirely on this symbolic data structure. We present several case studies which demonstrate the superiority of CASPA over sparse-matrix-based process algebra tools. Furthermore, CASPA is compared to other symbolic modelling tools.

[1]  G. Ciardo,et al.  ON THE USE OF KRONECKER OPERATORS FOR THE SOLUTION OF GENERALIZED STOCHASTIC PETRI NETS , 1996 .

[2]  William H. Sanders,et al.  Dependability Evaluation Using Composed SAN-Based Reward Models , 1992, J. Parallel Distributed Comput..

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

[4]  Marta Z. Kwiatkowska,et al.  PRISM: Probabilistic Symbolic Model Checker , 2002, Computer Performance Evaluation / TOOLS.

[5]  Matthias Kuntz,et al.  Deriving Symbolic Representations from Stochastic Process Algebras , 2002, PAPM-PROBMIV.

[6]  R. I. Bahar,et al.  Algebraic decision diagrams and their applications , 1993, Proceedings of 1993 International Conference on Computer Aided Design (ICCAD).

[7]  Kishor S. Trivedi,et al.  Stochastic Petri Net Models of Polling Systems , 1990, IEEE J. Sel. Areas Commun..

[8]  Holger Hermanns,et al.  Compositional performance modelling with the TIPPtool , 2000, Perform. Evaluation.

[9]  Joost-Pieter Katoen,et al.  Faster and Symbolic CTMC Model Checking , 2001, PAPM-PROBMIV.

[10]  William H. Sanders,et al.  Symbolic state-space exploration and numerical analysis of state-sharing composed models , 2004 .

[11]  Stephen Gilmore,et al.  A unified tool for performance modelling and prediction , 2003, Reliab. Eng. Syst. Saf..

[12]  David Anthony Parker,et al.  Implementation of symbolic model checking for probabilistic systems , 2003 .

[13]  H. Hermanns,et al.  Syntax , Semantics , Equivalences , and Axioms for MTIPP y , 1994 .

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

[15]  Randal E. Bryant,et al.  Graph-Based Algorithms for Boolean Function Manipulation , 1986, IEEE Transactions on Computers.

[16]  Holger Hermanns,et al.  On the use of MTBDDs for performability analysis and verification of stochastic systems , 2003, J. Log. Algebraic Methods Program..

[17]  Rajeev Alur,et al.  A Temporal Logic of Nested Calls and Returns , 2004, TACAS.

[18]  Marta Z. Kwiatkowska,et al.  Probabilistic symbolic model checking with PRISM: a hybrid approach , 2004, International Journal on Software Tools for Technology Transfer.

[19]  Christel Baier,et al.  Symbolic Model Checking for Probabilistic Processes , 1997, ICALP.

[20]  Enrico Macii,et al.  Algebric Decision Diagrams and Their Applications , 1997, ICCAD '93.

[21]  David Clark,et al.  Safety and Security Analysis of Object-Oriented Models , 2002, SAFECOMP.