A Study on Software Reliability Assessment Model of Superposition NHPP

중첩 NHPP를 이용한 소프트웨어 신뢰도 평가 모형 연구

  • Kim, Do-Hoon (Department of Applied Information Statistics, Kyonggi University) ;
  • Nam, Kyung-H. (Department of Applied Information Statistics, Kyonggi University)
  • 김도훈 (경기대학교 응용정보통계학과) ;
  • 남경현 (경기대학교 응용정보통계학과)
  • Published : 2008.03.31

Abstract

In this paper, we propose a software reliability growth model based on the superposition cause in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

Keywords

References

  1. Brocklehurst, S., Lu, M., and Littlewood, B.(1992), Combination of Predictions Obtained from Different Software Reliability Growth Models. Proceedings of the 10th annual Software Reliability Symposium, Denver, Colorado
  2. Chang, I. P.(1997), An analysis of software reliability with change-point models. NSC 85-2121-M031-003, National Science Council, Taiwan
  3. Fenton, N. E., Pfleeger, S. L.(1997), Software Metrics: A Rigorous and Practical Approach. PWS Publishing Company, Boston
  4. Fujiwara, T., Yamada, S.(2003), A testing-domain-dependent software reliability growth model for imperfect debugging environment and its evaluation of goodness-of-fit. Electronics and Communications in Japan, Part 3, Vol. 86, No. 1, pp. 11-18
  5. Goel, A. L. and Okumoto, K(1979), Time-dependent error-detection rate model for software reliability and other performance measures. IEEE Trans. on Reliability, Vol. R-28, No. 3, pp. 206-211 https://doi.org/10.1109/TR.1979.5220566
  6. Hinkley, D. V.(1970), Inference about the change-point in a sequence of random variables. Biometrika, Vol. 57, 206-211
  7. Lyu, M. R., and Nikora, A.(1992), Applying Reliability Models More Effectively, IEEE Software, 9(4)
  8. Malaiya, Y. K., and Srimani, P. K.(1992), Software Reliability Models : Theoretical Developments, Evaluation and Applications, IEEE Computer Society Press, CA.
  9. Musa, J. D., Iannino, A., Okumoto, K.(1987), Software reliability measurement prediction application. McGraw-Hill, New York
  10. Osaki, S.(1982), Nonhomogeneous error detection rate models for software reliability growth, in Stochastic Models in Reliability Theory, Osaki, S., Hatoyama, Y.(eds.), pp. 120-143
  11. Ohtera, H, Yamada, S., Narihisa, H(1990), Software reliability growth model for testing domain. Trans. IEICE, J73-D-I, 170-174
  12. Ohtera, H, Yamada, S., Ohba, M.(1990), Software reliability growth model with testing-domain and comparison of goodness-of-fit. Int. Symp. Reliability and Maintainability, 289-294
  13. Pham, H.(1993), Software reliability assessment: Imperfect debugging and multiple failure types in software development. EG&G-RAMM-10737, Idaho National Engineering Laboratory
  14. Pham, H. and Nordmann, L. and Zhang, X.(1999), "A General Imperfect-Software-Debugging Model with S-Shaped Fault-Detection Rate", IEEE Trans. Rel., Vol. 48, No. 2, pp. 169-75 https://doi.org/10.1109/24.784276
  15. Ross, S. M.(1997), Stochastic Processes(6nd ed.) John wiley & Sons, New York
  16. Shyur, H. J.(2003), A stochastic software reliability model with imperfect debugging and change-point, The Journal of System and Software, Vol. 66, pp. 135-141 https://doi.org/10.1016/S0164-1212(02)00071-7
  17. Software reliability growth models incorporating imperfect debugging with introduced faults. Electronics and Communications in Japan, Part 3, Vol. 81, No. 4, pp. 33-41
  18. Software reliability models : Theoretical developments, Evaluation and Applications, IEEE Computer Society Press, CA
  19. Yamada, S., Ohba, M. and Osaki, S.(1983), S-shaped reliability growth modeling for software error detection. IEEE Trans. on Reliability, Vol. R-32, No. 5, pp. 475-478, 484 https://doi.org/10.1109/TR.1983.5221735
  20. Yamada, S., Osaki, S.(1983), A reliability assessment method for software products in operational phase - Proposal of an accelerated life testing model, Electronics and Communications in Japan, Part 3, Vol. 84, No. 8, pp. 294-301
  21. Yamada, S., Tokuno, K, and Osaki, S.(1992), Imperfect debugging models with fault introduction rate for software reliability assessment. International Journal of System Science, Vol. 23. pp. 2241-2252 https://doi.org/10.1080/00207729208949452
  22. Zhao, M.(1993), Change-point problems in software and hardware reliability, Commun. Statistical-Theory Math. Vol. 22, pp. 757-768 https://doi.org/10.1080/03610929308831053