Journal of Korea Society of Digital Industry and Information Management (디지털산업정보학회논문지)

Korea Society of Digital Industry and Information Management (디지털산업정보학회)
권호 표지

The Comparative Study of NHPP Software Reliability Model Exponential and Log Shaped Type Hazard Function from the Perspective of Learning Effects

지수형과 로그형 위험함수 학습효과에 근거한 NHPP 소프트웨어 신뢰성장모형에 관한 비교연구

  • 김희철 (남서울대학교 산업경영공학과)
  • Published : 2012.06.30
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Abstract

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. 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 could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

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, "Time-dependent fault detection rate model for software and other performance measures," IEEE Trans Reliab. 28, 1978, pp. 206-11.
  3. Yamada S, Ohba H. "S-shaped software reliability modeling for software error detection," IEEE Trans Reliab, 32, 1983, pp. 475-484.
  4. Zhao M. "Change-point problems in software and hardware reliability," Commun. Stat Theory Methods, 22(3), 1993, pp. 757-768. https://doi.org/10.1080/03610929308831053
  5. Shyur H-J. "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 C-Y. "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. Kuei-Chen, C., YeuShiang, 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
  9. Hee-Cheul KIM and Hyoung-Keun Park, "Exponentiated Exponential Software Reliability Growth model," International Journal of Advancements in Computing Technology, Volume 1, Number 2, 2009, pp. 57-64.
  10. Musa, J. D, Iannino, A. and Okumoto, K. "Software Reliability: Measurement, Prediction, Application," McGraw Hill, New York, 1987, pp. 289-291.
  11. Kuo, L. and Yang, T. Y, "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
  12. 김희철, "NHPP 극값 분포 소프트웨어 신뢰모형에 대한 학습효과 기법 연구," 디지털산업정보학회 논문지, 제 7권, 제 2호, 2011, pp. 18.
  13. Y. HAYAKAWA and G. TELFAR "Mixed Poisson-Type Processes with Application in Software Reliability," Mathematical and Computer Modelling, 31, 2000, pp. 151-156. https://doi.org/10.1016/S0895-7177(00)00082-0
  14. 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.
  15. 이상식, 김희철, "혼합와이블 NHPP 모형에 근 거한 소프트웨어 최적방출시기에 관한 연구," 디지털산업정보학회 논문지, 제 6권, 제 2호, 2010, pp. 183-191.