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Programmable Electronic System Analysis Technique in Safety Critical Applications

  • M. J. P. van der Meulen
  • T. Stålhane
  • B. Cole
Conference paper

Abstract

The PESANTE1 project intends to arrive at an integral approach towards PES2 assessment. Elicitation of knowledge on relations between PES characteristic and functioning is the first step. Here categorical analysis plays a major role. The results of this phase will be used to tune a Bayesian inference network. This network is able to assess PESs given an amount of information on the PES characteristics. The techniques chosen are able to cope with heterogeneous and missing data. PESANTE will cover software and hardware aspects, as well as the human factor. Also, it can indicate the value of information to be procured next; this makes sure a balanced assessment is being made.

Keywords

Human Factor Categorical Analysis Knowledge Elicitation Human Dependability Safety Critical Application 
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.
    MIL-HDBK-217, Military Handbook, Reliability Prediction of Electronic Equipment, Rome Air Development Center, Griffiss Air Force Base, New York.Google Scholar
  2. 2.
    Stålhane, T., M.J.P. van der Meulen & B. Cole, Reliability Assessment for Programmable Electronic Systems using Subjective and Objective Categorical Data, Proceedings PCPI ’93, p101–8, Düsseldorf, Germany.Google Scholar
  3. 3.
    O’Connor, P.D.T., Reliability Prediction: Help or Hoax? Solid State Technology, p59–61, August 1990.Google Scholar
  4. 4.
    Bendell, A, & P. Mellor, Software Reliability; State of the Art Report, Pergamon Infotech Ltd., 1986.Google Scholar
  5. 5.
    A Resource Guide for the Process Safety Code of Management Practices, Responsible Care, Chemical Manufacturers Association, October 1990.Google Scholar
  6. 6.
    Majone, G. & E.S. Quade (ed.), Pitfalls of Analysis, John Wiley & Sons, New York, 1980. ISBN 0-471-27746-0.Google Scholar
  7. 7.
    Gifi, A., Nonlinear Multivariate Analysis, John Wiley & Sons, New York, 1980, ISBN 0-471-92620-5.zbMATHGoogle Scholar
  8. 8.
    Neil, M., Multivariate Assessment of Software Products. In: The Journal of Software Testing, Verification and Reliability, Vol. 1., (4) 17–37, 1992.Google Scholar
  9. 9.
    Bendell T., The Use of Exploratory Data Analysis Techniques for Software Reliability Assessment and Prediction.Google Scholar
  10. 10.
    Horvitz, E.J., J.S. Breese & M. Henrion, Decision Theory in Expert Systems and Artificial Intelligence, Knowledge Systems Laboratory, Technical Report No. KSL-88-13, Stanford University, California, July 1988.Google Scholar

Copyright information

© Springer-Verlag London Limited 1993

Authors and Affiliations

  • M. J. P. van der Meulen
    • 1
  • T. Stålhane
    • 2
  • B. Cole
    • 3
  1. 1.Department of Industrial Safety Institute for Environmental and Energy ResearchThe Netherlands Organization for Applied Scientific Research TNOApeldoornThe Netherlands
  2. 2.SINTEF DELABTrondheimNorway
  3. 3.Software Metrics LaboratoryGlasgow Caledonian UniversityGlasgowScotland

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