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Compositional Prediction of Timed Behaviour for Process Control Architecture

  • Kenneth Chan
  • Iman Poernomo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5581)

Abstract

The timing of properties is an essential consideration in the design, implementation and maintenance of embedded software development. In this paper, we present an approach to the prediction of timed and probabilistic nonfunctional properties of process control architectures. Our approach involves a novel compositional approach to model checking of statements in Probabilistic Computational Tree Logic (PCTL).

Keywords

Model Check Atomic Proposition Process Control System Compositional Approach Behavioural Description 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Becker, S., Koziolek, H., Reussner, R.: The palladio component model for model-driven performance prediction. Journal of Systems and Software 82(1), 3–22 (2009)CrossRefGoogle Scholar
  2. 2.
    Chan, K., Poernomo, I.H., Schmidt, H., Jayaputera, J.: A model-oriented framework for runtime monitoring of nonfunctional properties. In: Reussner, R., Mayer, J., Stafford, J.A., Overhage, S., Becker, S., Schroeder, P.J. (eds.) QoSA 2005 and SOQUA 2005. LNCS, vol. 3712, pp. 38–52. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Genssler, T., Christoph, A., Schulz, B.: PECOS in a nutshell (2002)Google Scholar
  4. 4.
    Hansson, H., Jonsson, B.: A logic for reasoning about time and reliability. Formal Aspects of Computing 6(5), 512–535 (1994)CrossRefzbMATHGoogle Scholar
  5. 5.
    Poernomo, I., Schmidt, H.W., Jayaputera, J.: Verification and prediction of timed probabilistic properties over the dmtf cim. International Journal of Cooperative Information Systems 15(4), 633–658 (2006)CrossRefGoogle Scholar
  6. 6.
    Reussner, R., Schmidt, H., Poernomo, I.: Reliability prediction for component-based software architectures. Journal of Systems and Software – Special Issue of Software Architecture - Engineering Quality Attributes 66(3), 241–252 (2003)Google Scholar
  7. 7.
    Schmidt, H.W., Krämer, B.J., Poernomo, I.H., Reussner, R.: Predictable component architectures using dependent finite state machines. In: Wirsing, M., Knapp, A., Balsamo, S. (eds.) RISSEF 2002. LNCS, vol. 2941, pp. 310–324. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Schmidt, H.W., Peake, I.D., Xie, J., Thomas, I., Krämer, B.J., Fay, A., Bort, P.: Modelling predictable component-based distributed control architectures. In: Proc. Ninth IEEE International Workshop on Object-Oriented Real-Time Dependable Systems (WORDS 2003), pp. 339–346. IEEE, Los Alamitos (2004)Google Scholar
  9. 9.
    Younes, H., Simmons, R.: Probabilistic verification of discrete event systems using acceptance sampling. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, pp. 223–235. Springer, Heidelberg (2002)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Kenneth Chan
    • 1
  • Iman Poernomo
    • 1
  1. 1.Department of Computer ScienceKing’s College London StrandLondonUK

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