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Nonhomogeneous Error Detection Rate Models for Software Reliability Growth

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Stochastic Models in Reliability Theory

Part of the book series: Lecture Notes in Economics and Mathematical Systems ((LNE,volume 235))

Abstract

Software reliability growth models with nonhomogeneous error detection rate are discussed. The models provide a plausible description in case that the software reliability growth is influenced by two types of errors: Types 1 and 2 errors. Type 1 (Type 2) errors are easy (difficult) to be detected. The software reliability growth models considered here are described by a nonhomogeneous Poisson process. First, the software reliability growth model which uses the testing time as the unit of error detection period Is discussed. The error detection rate per error for such an error detection process Is a time-dependent function. The meaningful assessment measures for software reliability are presented. The model parameters are estimated by a method of maximum likelihood. The asymptotic properties of the maximum likelihood estimates of the model parameters are derived and their application to the estimation of the assessment measures for software reliability is obtained. The optimum release policies for operational use of a software system based on the model are presented. Finally, the discrete software reliability growth modeling with two types of errors is discussed. The number of test runs instead of the testing time is used as the unit of the error detection period.

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References

  1. L.J. Bain, Statistical Analysis of Reliability and Life-Testing Models, Marcel Dekker, Inc., New York, 1978.

    MATH  Google Scholar 

  2. L.H. Crow, “On tracking reliability growth,” Proc. 1975 Annu. Reliability and Maintainability Symp., Washington, D.C., January 1975, PP. 438-443.

    Google Scholar 

  3. J.T. Duane, “Learning curve approach to reliability monitoring,” IEEE Trans. Aerosp., vol. 2, April 1964, pp. 563–566.

    Article  Google Scholar 

  4. E.H. Forman and N.D. Singpurwalla, “Optimal time intervals for testing hypotheses on computer software errors,” IEEE Trans. Reliab., vol. R-28(3), August 1979, pp. 250–253.

    Article  Google Scholar 

  5. A.L. Goel and K. Okumoto, “A time dependent error detection rate model for a large scale software system,” Proc. 3rd USA-Japan Computer Conf., San Francisco, Ca., October 1978, pp. 35-40.

    Google Scholar 

  6. A.L. Goel and K. Okumoto, “Time-dependent error-detection rate model for software reliability and other performance measures,” IEEE Trans. Reliab., vol. R-28(.3), August 1979, pp. 206–211.

    Article  Google Scholar 

  7. Z. Jelinski and P.B. Moranda, “Software reliability research,” in Statistical Computer Performance Evaluation, W. Freiberger, Ed., Academic Press, New York, 1972, pp. 465–484.

    Google Scholar 

  8. W. Kremer, “Birth-death and bug counting,” IEEE Trans. Reliab., vol, R-32[1], April 1983, pp. 36–47.

    MathSciNet  Google Scholar 

  9. H.S. Koch and P, Kubat, “Optimal release time of computer software,” IEEE Trans, Software Eng., vol, SE-9(3), May 1983, pp. 323–327.

    Article  Google Scholar 

  10. B, Littlewood, “Theories of software reliability: How good are they and how can they be improved?” IEEE Trans. Software Eng., vol. SE-6(5), September 1983, pp. 489–500.

    Article  Google Scholar 

  11. B. Littlewood and J.L. Verrall, “A Bayesian reliability growth model for computer software,” Applied Statistics, vol, 22(3), 1973, pp. 332–346.

    Article  MathSciNet  Google Scholar 

  12. P.B. Moranda, “Event-altered rate models for general reliability analysis,” IEEE Trans, Reliab., vol. R-28(5), December 1979, pp. 376–381.

    Article  Google Scholar 

  13. J.D. Musa, “A theory of software reliability and its application,” IEEE Trans. Software Eng., vol. SE-1(3), September 1975, pp. 312–327.

    Google Scholar 

  14. J.D. Musa, “Software reliability measurement,” J. Syst. Software, vol. 1, 1980, pp. 223–241.

    Article  Google Scholar 

  15. E.C. Nelson, “Estimating software reliability from test data,” Microelectron. Reliab., vol. 17(1), 1978, pp. 67–74.

    Article  Google Scholar 

  16. W. Nelson, Applied Life Data Analysis, John Wiley & Sons, Inc., New York, 1982.

    Book  MATH  Google Scholar 

  17. M, Ohba and M. Kajiyama,“Inflect ion S-shaped software reliability growth model,” (in Japanese) IPS-Japan Proc. WGSE Meeting, vol. 28, February 1983.

    Google Scholar 

  18. M, Ohba and S, Yamada, “S-shaped software reliability growth models,” Proc. 4th Int. Conf. Reliability and Maintainability, Perros-Guirec, France, May 1984, pp. 430–436.

    Google Scholar 

  19. M. Ohba, S. Yamada, K. Takeda and S, Osaki, “S-shaped software reliability growth curve: How good is it?” Proc. COMPSAC 1982, Chicago, 111., November 1982, pp. 38-44.

    Google Scholar 

  20. K. Okumoto and A.L. Goel, “Optimum release time for software systems based on reliability and cost criteria,” J. Syst. Software, vol. 1, 1980, pp. 315–318.

    Article  Google Scholar 

  21. C.V. Ramamoorthy and F.B. Bastani, “Software reliability — Status and perspectives,” IEEE Trans. Software Eng., vol. SE-8(4), July 1982, pp. 354–371.

    Article  Google Scholar 

  22. S.M. Ross, Stochastic Processes, John Wiley & Sons, Inc., New York, 1983.

    MATH  Google Scholar 

  23. G.J. Schick and R.W. Wolverton, “An analysis of competing software reliability models,” IEEE Trans. Software Eng., vol. SE-4(2), March 1978, pp. 104–120.

    Article  Google Scholar 

  24. J.G. Shanthikumar, “A state-and time-dependent error occurrencerate software reliability model with imperfect debugging,” Proc. 1981 Nat. Computer Conf., 1981, pp. 311-315.

    Google Scholar 

  25. J.G. Shanthikumar and S. Tufekci, “Application of a software reliability model to decide software release time,” Microelectron. Reliab., vol. 23(1), 1983, pp. 41–59.

    Article  Google Scholar 

  26. M.L. Shooman, “Software reliability: Measurement and models,” Proc, 1975 Annu. Reliability and Maintainability Symp., Washington, D.C., January 1975, PP. 485-491.

    Google Scholar 

  27. S.A. Smith and S.S. Oren, “Reliability growth of repairable systems,” Naval Res. Logist. Q., vol. 27 (4) December 1980,pp. 539–547.

    Article  MathSciNet  Google Scholar 

  28. W.A. Thompson, Jr., “On the foundations of reliability,” Technometrics, vol. 23(1), February 1981, pp. 1–13.

    Article  MathSciNet  MATH  Google Scholar 

  29. S. Yamada and S. Osaki, “Software reliability growth models and their comparisons,” (in Japanese) Trans. IECE Japan, vol. J65-D(7), July 1982, pp. 906–912; also Systems. Computers. Controls, vol. 13 (4), 1982, pp. 42-49.

    Google Scholar 

  30. S. Yamada and S. Osaki, “Quantitative methods for assessing software reliability,” (in Japanese) Trans. IECE Japan, vol. J65-D(12), December 1982, pp. 1483–1490.

    Google Scholar 

  31. S. Yamada and S. Osaki, “S-shaped software reliability growth models with four types of software error data,” Int. J. Systems Sci., vol. 14(6), June 1983, pp. 683–692.

    Article  MATH  Google Scholar 

  32. S. Yamada, S. Osaki and H. Narihisa, “Software reliability growth modeling with number of test runs,” Trans. IECE Japan, vol. E-67(2), Pebruary 1984, pp, 79–83.

    Google Scholar 

  33. S. Yamada, H. Narihisa and S. Osaki, “Optimum release policies for a software system with a scheduled software delivery time,” Int, J. Systems Sci., to be published, 1984.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Graduate School of Systems Science, Okayama University of Science, Okayama 700, Japan

    Shigeru Yamada

  2. Department of Industrial and Systems Engineering, Hiroshima University, Higashi-Hiroshima 724, Japan

    Shunji Osaki

Authors
  1. Shigeru Yamada
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  2. Shunji Osaki
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Editor information

Editors and Affiliations

  1. Department of Industrial and Systems Engineering Faculty of Engineering, Hiroshima University, Higashi-Hiroshima 724, Japan

    Shunji Osaki

  2. Faculty of Business Administration, Senshu University, Kawasaki 214, Japan

    Yukio Hatoyama

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© 1984 Springer-Verlag Berlin Heidelberg

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Yamada, S., Osaki, S. (1984). Nonhomogeneous Error Detection Rate Models for Software Reliability Growth. In: Osaki, S., Hatoyama, Y. (eds) Stochastic Models in Reliability Theory. Lecture Notes in Economics and Mathematical Systems, vol 235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45587-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-45587-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-13888-4

  • Online ISBN: 978-3-642-45587-2

  • eBook Packages: Springer Book Archive

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