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Lomax 분포의 형상모수에 근거한 무한고장 NHPP 소프트웨어 신뢰성 모형에 관한 연구

A Study for NHPP Software Reliability Model of Lomax Distribution Based on Shape Parameter

  • Kim, Hee-Cheul (Division of Industrial & Management Engineering, Namseoul University) ;
  • Shin, Hyun Cheul (Division of Industrial & Management Engineering, Namseoul University)
  • 투고 : 2015.10.08
  • 심사 : 2015.10.15
  • 발행 : 2015.10.30

초록

소프트웨어 고장분석을 위한 비동질적인 포아송과정에서 결함당 고장발생률이 상수이거나, 단조 증가 또는 단조 감소하는 패턴을 가질 수 있다. 본 논문에서는 수리시점에서도 고장이 발생할 상황을 반영하는 무한고장 NHPP모형들을 비교 제시하였다. 소프트웨어 경제, 경영, 보험수리분야에서 많이 사용되는 Lomax분포에 근거한 무한고장 소프트웨어 신뢰성모형에 대한 비교문제를 제시하였다. 그 결과 형상모수가 비교적 큰 경우가 효율적으로 나타났다. 그리고 모수 추정법은 최우추정법을 이용하였고 모형선택은 평균제곱오차와 결정계수를 이용하였다. 이 연구를 통하여 소프트웨어 개발자들은 형상모수에 따른 소프트웨어 고장현상을 파악하는데 어느 정도 도움을 줄 수 있을 것으로 사료된다.

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, infinite failures NHPP models that repairing software failure point in time reflects the situation, was presented for comparing property. Commonly used in business, economics, and actuarial modeling based on Lomax distribution, software reliability of infinite failures was presented for comparison problem. The result is that a relatively large shape parameter was effectively. The parameters estimation using maximum likelihood estimation was conducted and Model selection was performed using the mean square error and the coefficient of determination. In this research, software developers to identify software failure property follows shape parameter, some extent be able to help is considered.

키워드

참고문헌

  1. 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
  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. http://www.math.wm.edu/-leemis/chart/UDR/UDR.html
  12. R.Satya Prasad,G. Sridevi, and K.Sita Kumari, "Assessing Pareto Type II Software Reliability using SPC ", International Journal of Computer Applications (0975 - 8887), Vol 62, No. 3, pp. 17-21, 2013. https://doi.org/10.5120/10060-4652
  13. 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
  14. 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.