The Journal of Korea Institute of Information, Electronics, and Communication Technology (한국정보전자통신기술학회논문지)

Korea Information Electronic Communication Technology (한국정보전자통신기술학회)
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The Comparative Study for Software Reliability Model Based on Finite and Infinite Failure Exponential Power NHPP

유한 및 무한고장 지수파우어 NHPP 소프트웨어 신뢰성모형에 대한 비교 연구

  • Kim, Hee-Cheul (Division of Industrial & Management Engineering, Namseoul University) ;
  • Shin, Hyun-Cheul (Division of Internet information, BaekSeok Culture University)
  • Received : 2015.06.02
  • Accepted : 2015.06.10
  • Published : 2015.06.30
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Abstract

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, finite failure NHPP models that assuming the expected value of the defect and infinite failures NHPP models that repairing software failure point in time reflects the situation, were presented for comparing property. Commonly used in the field of software reliability based on exponential power distribution software reliability model finite failures and infinite failures were presented for comparison problem. As a result, finite fault model is effectively infinite fault models, respectively. The parameters estimation using maximum likelihood estimation was conducted. In this research, software developers to identify software failure property some extent be able to help is considered.

소프트웨어 고장분석을 위한 비동질적인 포아송과정에서 결함당 고장발생률이 상수이거나, 단조 증가 또는 단조 감소하는 패턴을 가질 수 있다. 본 논문에서는 결함의 기대값을 가정하는 유한고장소프트웨어 NHPP모형과 수리시점에서도 고장이 발생할 상황을 반영하는 무한고장 NHPP모형들을 비교 제시하였다. 소프트웨어 신뢰성분야에서 많이 사용되는 지수파우어분포에 근거한 유한고장과 무한고장 소프트웨어 신뢰성모형에 대한 비교문제를 제시하였다. 그 결과 유한고장모형이 무한고장모형보다 효율적으로 나타났다. 그리고 모수추정법은 최우추정법을 이용하였다. 이 연구를 통하여 소프트웨어 개발자들은 소프트웨어 고장현상을 파악하는데 어느 정도 도움을 줄 수 있을 것으로 사료된다.

Keywords

References

  1. L. Kuo and T. Y. Yang., "Bayesian Computation of Software Reliability", Journal of the American Statistical Association, Vol.91, pp. 763-773, 1996. https://doi.org/10.1080/01621459.1996.10476944
  2. Gokhale, S. S. and Trivedi, K. S. A, "time/structure based software reliability model", Annals of Software Engineering. 8, pp. 85-121. 1999. https://doi.org/10.1023/A:1018923329647
  3. Goel A L, Okumoto K, "Time-dependent fault detection rate model for software and other performance measures", IEEE Trans. Reliab. 28, pp.206-11, 1978.
  4. Yamada S, Ohba H, "S-shaped software reliability modeling for software error detection", IEEE Trans. Reliab, 32, pp.475-484, 1983.
  5. Zhao M, "Change-point problems in software and hardware reliability", Commun. Stat. Theory Methods, 22(3), pp.757-768, 1993. https://doi.org/10.1080/03610929308831053
  6. Shyur H-J, "A stochastic software reliability model with imperfect debugging and change-point", J. Syst. Software 66, pp.135-141, 2003. https://doi.org/10.1016/S0164-1212(02)00071-7
  7. Pham H, Zhang X., "NHPP software reliability and cost models with testing coverage", Eur. J. Oper. Res, 145, pp.445-454, 2003.
  8. Huang C-Y, "Performance analysis of software reliability growth models with testing-effort and change-point", J. Syst. Software 76, pp. 181-194, 2005. https://doi.org/10.1016/j.jss.2004.04.024
  9. Kuei-Chen, C., Yeu-Shiang, H., and Tzai-Zang, L., "A study of software reliability growth from the perspective of learning effects", Reliability Engineering and System Safety 93, pp. 1410-1421, 2008. https://doi.org/10.1016/j.ress.2007.11.004
  10. Hee-Cheul KIM, "The Comparative Study of NHPP Half-Logistic Distribution Software Reliability Model using the Perspective of Learning Effects", Journal of Next Generation Information Technology, Vol. 4, No. 8, pp. 132-139, 2013.
  11. Hee-Cheul KIM, "The Comparative Study of NHPP Delayed S-Shaped and Extreme Value Distribution Software Reliability Model using the Perspective of Learning Effects", International Journal of Advancements in Computing Technology, Vol. 5, No.9, pp. 1210 -1218, 2013. https://doi.org/10.4156/ijact.vol5.issue9.143
  12. Kuei-Chen. C, Yeu-Shiang. H, and Tzai-Zang. L, "A study of software reliability growth from the perspective of learning effects", Reliability Engineering and System Safety 93, pp. 1410-1421, 2008. https://doi.org/10.1016/j.ress.2007.11.004
  13. http://www.math.wm.edu/-leemis/chart/UDR/UDR.html.
  14. Lawless, J. F, "Statistical Models and Methods for Lifetime Data", John Wiley & Sons, New York, 1981.
  15. Y. HAYAKAWA and G. TELFAR, "Mixed Poisson-Type Processes with Application in Software Reliability", Mathematical and Computer Modelling, 31, pp. 151-156, 2000. https://doi.org/10.1016/S0895-7177(00)00082-0
  16. Kim, Hee Cheul, "The Comparative Study of Software Optimal Release Time of Finite NHPP Model Considering Half-Logistic and Log-logistic Distribution Property", The Journal of Korea Society of Digital Industry and Information, 9(2): 1-10, June, 2013.
  17. K. Kanoun and J. C. Laprie, "Handbook of Software Reliability Engineering", M.R.Lyu, Editor, chapter Trend Analysis. McGraw-Hill New York, NY, pp. 401-437, 1996.