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Elicitation and Validation of Graphical Dependability Models

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Computer Safety, Reliability, and Security (SAFECOMP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2788))

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Abstract

We discuss elicitation and validation of graphical dependency models of dependability assessment of complex, computer-based systems. Graphical (in)dependency models are network-graph representations of the assumed conditional dependences (statistical associations) of multivariate probability distributions. These powerfully ‘visual’, yet mathematically formal, representations have been studied theoretically, and applied in varied contexts, mainly during the last 15 years. Here, we explore the application of recent Markov equivalence theory, of such graphical models, to elicitation and validation of dependability assessment expertise. We propose to represent experts’ statements by the class of all Markov non-equivalent graphical models consistent with those statements. For any one of these models, we can produce alternative, but formally Markov equivalent, graphical representations. Comparing different graphical models highlights subsets of their underlying assumptions.

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References

  1. Lyu, M.R. (ed.): Handbook of Software Reliability Engineering. IEEE Computer Society Press, Los Alamitos (1996) (with enclosed CD containing software failure data sets)

    Google Scholar 

  2. Littlewood, B., Strigini, L.: Software reliability and dependability: a roadmap. In: Finkelstein, A. (ed.) The Future of Software Engineering. State of the Art Rep. given at 22nd Int. Conf. on Softw. Engin., Limerick, pp. 177–188. ACM Press, New York (2000), http://www.csr.city.ac.uk/people/lorenzo.strigini/ls.papers/ICSE2000SWreliabRoadmap/

  3. Butler, R.W., Finelli, G.B.: The infeasibility of quantifying the reliability of lifecritical real-time software. IEEE Trans. on Software Engineering 19, 3–12 (1993)

    Article  Google Scholar 

  4. Littlewood, B., Strigini, L.: Validation of ultra-high dependability for softwarebased systems. Commun. Assoc. Computing Machinery 36, 69–80 (1993)

    Google Scholar 

  5. Fenton, N.E., Littlewood, B., Neil, M., Strigini, L., Sutcliffe, A., Wright, D.: Assessing dependability of safety critical systems using diverse evidence. IEE Proceedings on Software Engineering 145, 35–39 (1998)

    Article  Google Scholar 

  6. Fenton, N., Littlewood, B., Neil, M., Strigini, L., Wright, D., Courtois, P.J.: Bayesian belief network model for the safety assessment of nuclear computer-based systems, City University (1998) 2nd Year Proj. Deliverable of ESPRIT DeVa project 20072, http://www.newcastle.research.ec.org/deva/papers/5B.ps

  7. Wright, D.R.: Elicitation & validation of graphical dependability models, City Univer (2003), ROPA Proj. Rep., www.csr.city.ac.uk/people/david.wright/ropa/

  8. Littlewood, B., Strigini, L., Wright, D., Courtois, P.J.: Examination of Bayesian belief network for safety assessment of nuclear computer-based systems, CSR, City University (1998) 3rd Year Project Deliverable of ESPRIT DeVa project 20072. T.R. No. 70, http://www.newcastle.research.ec.org/deva/trs/index.html

  9. Pearl, J.: Probabilistic Reasoning in Intelligent Syst.: Networks of Plaus. Inference. Math. & Its Applics. Morgan Kauf., San Mateo (1988) Rev. 2nd print. 1991

    Google Scholar 

  10. Andersen, S.K., Olesen, K.G., Jensen, F.V., Jensen, F.: Hugin—a shell for building Bayesian belief universes for expert systems. In: Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, Detroit, pp. 1080–1084 (1989)

    Google Scholar 

  11. Cowell, R.G., Dawid, A.P., Lauritzen, S.L., Spiegelhalter, D.J.: Probabilistic Networks and Exp. Syst. Stat. for Engin. & Inf. Sci. Springer, New York (1999)

    Google Scholar 

  12. Real-world applics. of Bayesian networks. Comm. ACM, Spec. Iss. 38, 24–57 (1995)

    Google Scholar 

  13. Lauritzen, S.L.: Graphical Models. Oxfd. Stat. Sci. Ser. Clarend. Pr., Oxfd (1996)

    Google Scholar 

  14. Dawid, A.: Some misleading arguments involving conditional independence. Journal Royal Statistical Society, Series B 41, 249–252 (1979)

    MathSciNet  Google Scholar 

  15. Dawid, A.P.: Conditional independence in statistical theory. Journal Royal Statistical Society, Series B 41, 1–31 (1979) (with discussion)

    Google Scholar 

  16. Shafer, G.: Probabilistic Expert Systems. In: CBMS-NSF Regional Conf. Ser. In Applied Math. Society for Industrial & Applied Mathematics, Philadelphia (1996)

    Google Scholar 

  17. Dawid, A.P.: Conditional independence for statistical operations. Annals of Statistics 8, 598–617 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  18. Studený, M.: On mathematical description of probabilistic conditional independence structures, Dr. of Science Thesis, Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague (2001)

    Google Scholar 

  19. Wermuth, N., Lauritzen, S.L.: On substantive research hypotheses, conditional independence graphs and graphical chain models. Journal Royal Statistical Society, Series B 52, 21–72 (1990) (with discussion)

    Google Scholar 

  20. Studený, M.: Conditional independence relations have no finite complete characterisation. In: Trans. 11th Prague Conference on Information Theory, Statistical Decision Functions and Random Processes, pp. 377–396. Kluwer, Dordrecht (1992)

    Google Scholar 

  21. Lauritzen, S.L., Richardson, T.S.: Chain graph models and their causal interpretation. Journal Royal Statistical Society, Series B 64, 321–361 (2002) (with discussion)

    Google Scholar 

  22. Volf, M., Studený, M.: A graphical characteristn. of the largest chain graphs. Int. J. Approx. Reas. 20, 209–236 (1999), ftp://ftp.utia.cas.cz/pub/staff/studeny/volstu.ps

    Article  MATH  Google Scholar 

  23. Frydenberg, M.: The chain graph Markov property. Scandinavian Journal of Statistics 17, 333–353 (1990)

    MATH  MathSciNet  Google Scholar 

  24. Cameron, P.J.: Combinatorics: Topics, Techniques, Algorithms. CUP, Cambridge (1994)

    Google Scholar 

  25. Andersson, S.A., Madigan, D., Perlman, M.D.: On the Markov equivalence of chain graphs, undirected graphs, and acyclic digraphs. Scand. J. Stat. 24, 81–102 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  26. Andersson, S.A., Madigan, D., Perlman, M.D.: A characterization of Markov equivalence classes for acyclic digraphs. Annals of Statistics 25, 505–541 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  27. Maple ver. V.5 (packages Perm, Linalg, Networks), http://www.maplesoft.com/

  28. McKay, B.D.: nauty user’s guide (ver. 1.5), Tech. report TR-CS-90-02. Australian National University, Comp. Sci. Dept. (1990), http://cs.anu.edu.au/~bdm/nauty/

  29. Soicher, L.H.: GRAPE: a system for computing with graphs and groups. In: Finkelstein, L., Kantor, W.M. (eds.) Groups and Computation. DIMACS Ser. in Discrete Math. & Theor. Comp. Sci., Amer. Math. Soc, vol. 11, pp. 287–291 (1993), http://www-groups.dcs.st-and.ac.uk/~gap/Share/grape.html GRAPE is a package developed for the system: GAP—Groups, Algorithms, & Programming, Ver. 4.2 http://www.gap-system.org/

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Wright, D. (2003). Elicitation and Validation of Graphical Dependability Models. In: Anderson, S., Felici, M., Littlewood, B. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2003. Lecture Notes in Computer Science, vol 2788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39878-3_2

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  • DOI: https://doi.org/10.1007/978-3-540-39878-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20126-7

  • Online ISBN: 978-3-540-39878-3

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