Analysis of Software Failure Data

  • Refik Soyer
Conference paper
Part of the NATO ASI Series book series (volume 154)

Summary

In this chapter we discuss Bayesian analysis of software failure data by using some of the software reliability models introduced by Singpurwalla and Soyer (1996). In so doing, we present details concerning Bayesian inference in these models, and discuss what insights can be obtained from the models when they are applied to real data. We also present approximation procedures that facilitate the Bayesian analysis and discuss model comparison.

Keywords

Autoregressive processes Bayesian inference data augmentation Gibbs sampling hierarchical models Kalman filtering point processes posterior approximations 
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References

  1. Campodónico, S.: Software for a Bayesian Analysis of the Logarithmic-Poisson Execution Time Model. Technical Report GWU/IRRA/TR-93/5. Institute for Reliability and Risk Analysis, The George Washington University (1993)Google Scholar
  2. Campodónico, S., Singpurwalla, N.D.: A Bayesian Analysis of the Logarithmic-Poisson Execution Time Model Based on Expert Opinion and Failure Data. IEEE Trans. Soft. Eng. SE-20, 677–683 (1994)Google Scholar
  3. Chen, Y., Singpurwalla, N.D.: A Non-Gaussian Kalman Filter Model for Tracking Software Reliability. Statistica Sinica 4, 535–548 (1994)MATHGoogle Scholar
  4. Deely, J.J., Lindley, D.V.: Bayes Empirical Bayes. J. Amer. Statist. Assoc. 76, 833–841 (1981)MathSciNetMATHCrossRefGoogle Scholar
  5. Gelfand, A.E., Smith, A.F.M.: Sampling-Based Approaches to Calculating Marginal Densities. J. Amer. Statist. Assoc. 85, 398–409 (1990)MathSciNetMATHCrossRefGoogle Scholar
  6. Gilks, W.R., Wild, P.: Adaptive Rejection Sampling for Gibbs Sampling. Appl. Statist. 41, 337–348 (1992)MATHGoogle Scholar
  7. Goel, A.L.: Software Reliability Models: Assumptions, Limitations, and Applicability. IEEE Trans. Soft. Eng. SE-11, 1411–1423 (1985)Google Scholar
  8. Jelinski, Z., Moranda, P.: Software Reliability Research. In: Freiberger, W. (ed.): Statistical Computer Performance Evaluation. New York: Academic Press 1972, pp. 465–484Google Scholar
  9. Kuo, L., Yang, T.Y.: Bayesian Computation of Software Reliability. J. Comp. and Graph. Statist. 4, 65–82 (1995)Google Scholar
  10. Lindley, D.V.: Approximate Bayesian Methods. Trabajos Estadistica 31, 223–237 (1980)CrossRefGoogle Scholar
  11. Littlewood, B., Verall, J.L.: A Bayesian Reliability Growth Model for Computer Software. Appl. Statist. 22, 332–346 (1973)CrossRefGoogle Scholar
  12. Mazzuchi, T.A., Soyer, R.: Software Reliability Assessment Using Posterior Approximations. Proceedings of the 19th Symposium. Computer Science and Statistics 1987, pp. 248–254Google Scholar
  13. Mazzuchi, T.A., Soyer, R.: A Bayes Empirical-Bayes Model for Software Reliability. IEEE Trans. Rel. R-37, 248–54 (1988)Google Scholar
  14. Meinhold, R.J., Singpurwalla, N.D.: Bayesian Analysis of a Commonly Used Model for Describing Software Failures. Statistician 32, 168–173 (1983)CrossRefGoogle Scholar
  15. Merrick J., Singpurwalla, N.D.: The Role of Decision Analysis in Software Engineering. In this volume (1996), pp. 368–388Google Scholar
  16. Musa, J.D.: Software Reliability Data. IEEE Computing Society Repository (1979)Google Scholar
  17. Musa, J.D., Okumoto, K.: A Logarithmic Poisson Execution Time Model for Soft-ware Reliability Measurement. Proceedings of the 7th International Conference on Software Engineering. Orlando 1984, pp. 230–37Google Scholar
  18. Roberts, H.V.: Probabilistic Prediction. J. Amer. Statist. Assoc. 60, 50–61 (1965)MathSciNetMATHCrossRefGoogle Scholar
  19. Singpurwalla, N.D., Soyer, R.: Assessing (Software) Reliability Growth Using a Random Coefficient Autoregressive Process and its Ramifications. IEEE Trans. Soft. Eng. SE-11, 1456–1464 (1985)Google Scholar
  20. Singpurwalla, N.D., Soyer, R.: Non-Homogeneous Autoregressive Processes for Tracking (Software) Reliability Growth, and Their Bayesian Analysis. J. Roy. Statist. Soc. B 54, 145–156 (1992)Google Scholar
  21. Singpurwalla, N.D., Soyer, R.: Assessing the Reliability of Software: An overview. In this volume (1996), pp. 345–367Google Scholar
  22. Tierney, L., Kadane, J.B.: Accurate Approximations for Posterior Moments and Marginal Densities. J. Amer. Statist. Assoc. 81, 82–86 (1986)MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Refik Soyer
    • 1
  1. 1.Department of Management ScienceThe George Washington UniversityUSA

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