The Comparative Study for Property of Learning Effect based on Truncated time and Delayed S-Shaped NHPP Software Reliability Model

절단고정시간과 지연된 S-형태 NHPP 소프트웨어 신뢰모형에 근거한 학습효과특성 비교연구

  • 김희철 (남서울대학교 산업경영공학과)
  • Published : 2012.12.30

Abstract

In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than autonomous errors-detected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.

Keywords

References

  1. Gokhale, S. S. and Trivedi, K. S. "A time / structure based software reliability model," Annals of Software Engineering. 8, 1999, pp. 85-121. https://doi.org/10.1023/A:1018923329647
  2. Goel AL, Okumoto K, "Timedependent fault detection rate model for software and other performance measures," IEEE Trans Reliab. 28, 1978, pp. 206-11.
  3. Yamada S, Ohba H. "Sshaped software reliability modeling for software error detection," IEEE Trans Reliab, 32, 1983, pp. 475-484.
  4. Zhao M. "Changepoint problems in software and hardware reliability," Commun. Stat Theory Methods, 22(3), 1993, pp. 757-768. https://doi.org/10.1080/03610929308831053
  5. Shyur HJ. "A stochastic software reliability model with imperfect debugging and changepoint," J Syst. Software 66, 2003, pp. 135-141. https://doi.org/10.1016/S0164-1212(02)00071-7
  6. Pham H, Zhang X. "NHPP software reliability and cost models with testing coverage," Eur J. Oper Res, 145, 2003, pp. 445-454.
  7. Huang CY. "Performance analysis of software reliability growth models with testingeffort and changepoint," J. Syst Software 76, 2005, pp. 181-194. https://doi.org/10.1016/j.jss.2004.04.024
  8. KueiChen, C., YeuShiang, H., and TzaiZang, 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
  9. Prince, D. R. and Vivekanandan, P., "TRUNCATED SOFTWARE RELIABILITY GROWTH MODEL", performance measure, Korean J. Comput. & Appl. Math. (Series A) Vol. 9, 2002, pp. 761-769.
  10. A. K. Sheikh, J. K. Boah, M. Younas., "Truncated Extreme value model for popeline Reliability", Reliability Engineering and system safety, Vol. 28, 1989, pp. 1-14.
  11. HeeCheul KIM and HyoungKeun Park, "Exponentiated Exponential Software Reliability Growth model," International Journal of Advancements in Computing Technology, Volume 1, Number 2, 2009, pp. 57-64.
  12. Musa, J. D, Iannino, A. and Okumoto, K. "Software Reliability: Measurement, Prediction, Application," McGraw Hill, New York, 1987, pp.289-291.
  13. Kuo, L. and Yang, T. Y, "Bayesian Computation of Software Reliability," Journal of the American Statistical Association, Vol. 91, 1996, pp. 763-773. https://doi.org/10.1080/01621459.1996.10476944
  14. 김희철, "NHPP 극값 분포 소프트웨어 신뢰모형에 대한 학습효과 기법 연구," 디지털산업정보학회 논문지, 제7권, 제 2호, 2011, pp. 1-8.
  15. 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
  16. Alaa Sheta, "Parameter Estimation of Soft ware Reliability Growth Models by Particle S warm Optimization," AIML Journal, Volume (7), Issue (1), June, 2007, pp. 55-61.
  17. 김희철, "다항 위험함수에 근거한 NHPP 소프트 웨어 신뢰성장모형에 관한 연구," 디지털산업정보학회 논문지, 제 7권, 제 4호, 2011, pp. 7-14.
  18. K. Kanoun, J. C. Laprie, "Handbook of Software Reliability Engineering," M. R. Lyu, Editor, chapter Trend Analysis. McGrawHill New York, NY, 1996, pp. 401-437.
  19. HeeCheul KIM and Jae-Wook Kim, "Truncated Log Shaped Type Software Reliability Growth Model," ICHIT 2012, LNCS, 7425, Springer-Verlag Berlin Heidelberg 2012, 2012, pp. 625-632,