DOI QR코드

DOI QR Code

Parameter Estimation and Comparison for SRGMs and ARIMA Model in Software Failure Data

  • Song, Kwang Yoon (Department of Computer Science and Statistics, Chosun University) ;
  • Chang, In Hong (Department of Computer Science and Statistics, Chosun University) ;
  • Lee, Dong Su (Department of Computer Science and Statistics, Chosun University)
  • 투고 : 2014.08.12
  • 심사 : 2014.09.25
  • 발행 : 2014.09.30

초록

As the requirement on the quality of the system has increased, the reliability is very important part in terms of enhance stability and to provide high quality services to customers. Many statistical models have been developed in the past years for the estimation of software reliability. We consider the functions for NHPP software reliability model and time series model in software failure data. We estimate parameters for the proposed models from three data sets. The values of SSE and MSE is presented from three data sets. We compare the predicted number of faults with the actual three data sets using the NHPP software reliability model and time series model.

키워드

참고문헌

  1. R. Kitchin and M. Dodge, "Code/space: Software and everyday life", The MIT Press, 2011.
  2. K. S. Lew, T. S. Dillon, and K. E. Forward, "Software complexity and its impact on software reliability", IEEE Trans. Softw. Eng., Vol. 14, pp. 1645-1655, 1988. https://doi.org/10.1109/32.9052
  3. T. Goradia, "Dynamic impact analysis: A costeffective technique to enforce error-propagation", Acm Sigsoft Softw. Eng. Notes, Vol. 18, pp. 171-181, 1993. https://doi.org/10.1145/174146.154269
  4. A. L. Goel and K. Okumoto, "Time dependent error detection rate model for software reliability and other performance measures," IEEE T. Reliab., Vol. R-28, pp. 206-211, 1979.
  5. H. Pham and X. Zhang, "An NHPP software reliability models and its comparison", Int. J. Rel. Qual. Saf. Eng., Vol. 4, pp. 269-282, 1997. https://doi.org/10.1142/S0218539397000199
  6. H. Pham, L. Nordmann, and X. Zhang, "A general imperfect software debugging model with S-shaped fault detection rate", IEEE T. Reliab., Vol. 48, pp. 169-175, 1999. https://doi.org/10.1109/24.784276
  7. S. Yamada, K. Tokuno, and S. Osaki, S, "Imperfect debugging models with fault introduction rate for software reliability assessment", Int. J. Syst. Sci., Vol. 23, pp. 2253-2264, 1992. https://doi.org/10.1080/00207729208949453
  8. K. Y. Song and I. H. Chang, "Parameter estimation and prediction for NHPP software reliability model and time series regression in software failure data", J. Chosun Natural Sci., Vol. 7, pp. 67-70, 2014. https://doi.org/10.13160/ricns.2014.7.1.67
  9. R. H. Shumway and D. S. Stoffer, "Time series analysis and its applications", Springer, 2006.
  10. W. S. William and Wei, "Time series analysis", Pearson, 2006.
  11. J. D. Musa, A. Iannino, and K. Okumoto, "Software reliability: measurement, prediction, application", McGraw-Hill, New York, 1987.
  12. C. Stringfellow and A. A. Andrews, "An empirical method for selecting software reliability growth models", Empirical Software Engineering, Vol. 7, pp. 319-343, 2002. https://doi.org/10.1023/A:1020515105175
  13. H. Pham, "System software reliability", Springer, 2006.