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Validation of a Software-Related Failure Mode Taxonomy

  • Alice Lee
  • Carol Smidts
  • Bin Li
  • Ming Li
Conference paper

Abstract

Probabilistic Risk Assessment (PRA) is a methodology used to determine the probability of failure or success of a system. PRA results are typically used to make decisions on life extensions, sub-systems upgrades, scheduling of maintenance activities, selection of design concepts, etc. Current PRA methodology accounts for the contributions of hardware systems and in some instances of operating and maintenance crews to risk. However, modern systems are heavily software dependent and this dependency seems to increase. Current PRA methodology neglects the impact of software components on risk. This paper describes initial efforts to address the software issue.

Keywords

Failure Mode Configuration Management Probabilistic Risk Assessment Failure Report Interaction Failure 
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.
    Li B., Li M., Smidts C., Integrating Software into PRA, in the 14th IEEE International Symposium on Software Reliability Engineering (ISSRE’2003), IEEE, Denver, 2003, pp 457–467.Google Scholar
  2. 2.
    Lee A., Chen K., Kube J., et al, PRA Modeling, Validation, and Application for Software, Report on Failure Taxonomy Validation, NASA Johnson Space Center, September, 2003.Google Scholar
  3. 3.
    Li B., Li M., Smidts C., Integrating Software into PRA: A Taxonomy of Software Related Failures, in the Sixth IEEE International Symposium on High Assurance Systems Engineering, Boca Raton, Florida, 2001.Google Scholar
  4. 4.
    Vesely B., Validating a PRA: the Different Types of Validation, NASA internal report, September, 2003.Google Scholar

Copyright information

© Springer-Verlag London 2004

Authors and Affiliations

  • Alice Lee
    • 1
  • Carol Smidts
    • 2
  • Bin Li
    • 2
  • Ming Li
    • 2
  1. 1.NASA- Johnson Space CenterHoustonUSA
  2. 2.Center for Reliability EngineeringUniversity of MarylandCollege ParkUSA

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