DOI QR코드

DOI QR Code

The Comparative Study based on Gompertz Software Reliability Model of Shape Parameter

곰페르츠형 형상모수에 근거한 소프트웨어 신뢰성모형에 대한 비교연구

  • 신현철 (백석문화대학교 인터넷 정보학부) ;
  • 김희철 (남서울대학교 산업경영공학과)
  • Received : 2014.05.07
  • Accepted : 2014.06.02
  • Published : 2014.06.30

Abstract

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.

Keywords

References

  1. Musa, J. D, Iannino, A. and Okumoto, K. "Software Reliability: Measurement, Prediction, Application," McGraw Hill, New York, 1987, pp. 289291.
  2. Gokhale, S. S. and Trivedi, K. S. "A time / structure based software reliability model," Annals of Software Engineering. 8, 1999, pp. 85121.
  3. Goel AL, Okumoto K, "Timedependent fault detection rate model for software and other performance measures," IEEE Trans Reliab, 28, 1978, pp. 20611.
  4. Yamada S, Ohba H. "Sshaped software reliability modeling for software error detection," IEEE Trans Reliab, 32, 1983, pp. 475484.
  5. Zhao M. "Changepoint problems in software and hardware reliability," Commun. Stat Theory Methods, 22(3), 1993, pp. 757768.
  6. Shyur HJ. "A stochastic software reliability model with imperfect debugging and changepoint," J Syst. Software 66, 2003, pp. 135141.
  7. Pham H, Zhang X. "NHPP software reliability and cost models with testing coverage," Eur J. Oper Res, 145, 2003, pp. 445454.
  8. Huang CY. "Performance analysis of software reliability growth models with testingeffort and changepoint," J. Syst Software 76, 2005, pp. 181194.
  9. http://en.wikipedia.org/wiki/Gompertz_ distribution
  10. 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), June, 2013, pp. 1-10.
  11. Hyun-Dai SHIN, Hee-Cheul KIM, "The Comparative Study of Software Optimal Release Time Based on NHPP Software Reliability Model using Exponential and Log Shaped Type for the Perspective of Learning Effects," IJACT: International Journal of Advancements in Computing Technology, Vol. 5, No. 12, 2013, pp. 120-129. https://doi.org/10.4156/ijact.vol5.issue1.14
  12. HeeCheul KIM and HyoungKeun Park, "Exponentiated Exponential Software Reliability Growth model," International Journal of Advancements in Computing Technology, Volume 1, Number 2, 2009, pp. 5764.
  13. 김희철, "NHPP 극값 분포 소프트웨어 신뢰모형에 대한 학습효과 기법 연구," 디지털산업정보학회 논문지, 제 7권, 제 2호, 2011, pp. 18.
  14. Hee-Cheul KIM, Hyoung-Keun Park, "The Comparative Study of Software Optimal Release Time Based on Burr Distribution. International Journal of Advancements in Computing Technology," Volume 2, Number 3, 2010, pp. 119-128. https://doi.org/10.4156/ijact.vol2.issue3.13
  15. 김희철, "다항 위험함수에 근거한 NHPP 소프트웨어 신뢰성장모형에 관한 연구," 디지털산업정보학회 논문지, 제 7권, 제 4호, 2011, pp. 714.
  16. 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, 2008, pp. 1410-1421. https://doi.org/10.1016/j.ress.2007.11.004
  17. R. Satya Prasad, K. R. H. Rao and R. R. L Kantha, Software Reliability Measuring using Modified Maximum Likelihood Estimation and SPC, International Journal of Computer Applications (0975-8887), Volume 21, No. 7, May, 2011, pp. 1-5.
  18. K. Kanoun, J. C. Laprie, "Handbook of Software Reliability Engineering," M. R. Lyu, Editor, chapter Trend Analysis. McGrawHill New York, NY, 1996, pp. 401437.