Methodology for UML Modeling and Formal Verification of Real-Time Systems

In the paper, we present a methodology developed in order to verify probabilistic timed properties related to dependability of real-time systems. The methodology is made of three essential steps. The first one is a UML profile called DAMRTS (dependability analysis models for real-time systems) designed using GME tool. The aim is to model a real-time system with qualitative and quantitative information related to its quality of service. In this profile, UML statecharts are used to represent the system behavior. An extension is introduced with probabilities, real-time requirements and nondeterministic choices. The second one proposes a translation from extended UML statecharts to probabilistic timed automata. In this step, synchronization by events is used in probabilistic timed automata to describe the concurrency in UML statecharts. The last one is about the probabilistic model checking. This requires specification of dependability properties with a suitable temporal logic.

[1]  Jacky Montmain,et al.  Formalisation of Quantitative UML models Using Continuous Time Markov Chains. , 2004 .

[2]  Zohar Manna,et al.  Formal verification of probabilistic systems , 1997 .

[3]  Jacky Montmain,et al.  UML models for dependability analysis of real-time systems , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[4]  Thomas A. Henzinger,et al.  Reactive Modules , 1996, Proceedings 11th Annual IEEE Symposium on Logic in Computer Science.

[5]  Marta Z. Kwiatkowska,et al.  Probabilistic Model Checking of Deadline Properties in the IEEE 1394 FireWire Root Contention Protocol , 2003, Formal Aspects of Computing.

[6]  Rajeev Alur,et al.  A Theory of Timed Automata , 1994, Theor. Comput. Sci..

[7]  Joost-Pieter Katoen,et al.  A Probabilistic Extension of UML Statecharts , 2002, FTRTFT.

[8]  Diego Latella,et al.  A stochastic extension of a behavioural subset of UML statechart diagrams , 2000, Proceedings. Fifth IEEE International Symposium on High Assurance Systems Engineering (HASE 2000).

[9]  Gabor Karsai,et al.  The Generic Modeling Environment , 2001 .

[10]  Stephen Gilmore,et al.  Performance modelling with UML and stochastic process algebras , 2002 .

[11]  Marta Z. Kwiatkowska,et al.  Model checking for probability and time: from theory to practice , 2003, 18th Annual IEEE Symposium of Logic in Computer Science, 2003. Proceedings..

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

[13]  Susanna Donatelli,et al.  A compositional semantics for UML state machines aimed at performance evaluation , 2002, Sixth International Workshop on Discrete Event Systems, 2002. Proceedings..

[14]  Arndt Lüder,et al.  Distributed intelligence for plant automation based on multi-agent systems: the PABADIS approach , 2004 .