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Coral: a tool for Compositional Reliability and Availability analysis †

Coral: a tool for Compositional Reliability and Availability analysis †. Hichem Boudali 1 , Pepijn Crouzen 2 , and Mari ë lle Stoelinga 1 . 1 Formal Methods and Tools group CS, University of Twente, NL . 2 Dependable Systems and Software group, CS, Saarland University, Germany.

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Coral: a tool for Compositional Reliability and Availability analysis †

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  1. Coral:a tool for CompositionalReliability and Availability analysis† Hichem Boudali1, Pepijn Crouzen2, and Mariëlle Stoelinga1. 1Formal Methods and Tools group CS, University of Twente, NL. 2Dependable Systems and Software group, CS, Saarland University, Germany

  2. Context & Motivation • Systems do fail • Reliability Engineering: • Analyze system reliability • Many formalisms: Petri nets, RBDs, DFTs, AADL, • DFTs: • Graphical, popular formalism • Unreliabilty = P[failure during mission time]

  3. Graphical, intuitive formalism Specify system failures in terms of component failure Tree/DAG leaves: basic events = component failures gates: failure propagation CORAL methodology formal semantics using IOIMCs Compositional modeling + verification state space reduction techniques Dynamic Fault trees road trip car phone engine tire 1 tire 2 tire 3 tire 4 spare

  4. Tool Chain mission time DFT C O R A L dft2bcg IOIMC models IOIMC model dft_eval dft2bcg SVL bcg_labels CTMC + goal state SVL DFT repository bcg_trans Unrealiability = P[failure during mission time]

  5. What is deep compositionality? f(G1) Failure 2/3 A B C S • Semantics of a DFT arises naturally ascomposition of the semantics of its building blocks Translation each gate gets IOIMC Composition f(G1) f(NE1) … f(NE4) • But: This may lead to huge models.

  6. Prototype tool chainCoral – DFT analysis composer: minimization CTMC composer: Composition dft2bcg: Translation 1325 states instead of 32757 states User-given ordering composer: Repeat dft_eval: Analysis Composition order matters Result: unreliability dft_eval: MC generation

  7. Tool Chain composition script mission time DFT C O R A L dft2bcg IOIMC models IOIMC model dft_eval dft2bcg SVL bcg_labels CTMC + goal state SVL DFT repository bcg_trans Unrealiability

  8. Case studies

  9. Lack of formal semantics semantics in terms of IOIMCs Each gate & BE has corresp. IOIMC DFT semantics = composition of gate semantics Lack of modularity severe restrictions on reuse of sub-models in larger models CORAL is much more liberal State space explosion problem use bisimulation to combate state space explosion CORAL: lifting previous drawbacks of DFTs road trip car phone engine tire 1 tire 2 tire 3 tire 4 spare

  10. Future work • Fully automated tool • Get rid of composition script • Order of composition matters  heuristics • More aggressive state reduction • Weaker equivalence, interface constraints, Phase-type minimization • Further extensions to DFT modeling capabilities • Extension to non-exponential distributions • New DFT building blocks • Simulation for DFTs • Apply deep compositionality to other engineering formalisms! • E.g. Architectural description languages like AADL

  11. References • H. Boudali, P. Crouzen, M. Stoelinga. “Dynamic Fault Tree analysis using Input/Output Interactive Markov Chains”, DSN 2007 proceedings. • H. Boudali, P. Crouzen, M. Stoelinga. “A compositional semantics for Dynamic Fault Trees in terms of Interactive Markov Chains”, ATVA 2007. • More info: • crouzen@alan.cs.uni-sb.de • hboudali@cs.utwente.nl • marielle@cs.utwente.nl

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