Journal of Information Technology Applications and Management

Korea Data Strategy Society (한국데이터전략학회)
권호 표지
DOI QR코드

DOI QR Code

A Comparative Study of the Parameter Estimation Method about the Software Mean Time Between Failure Depending on Makeham Life Distribution

메이크헴 수명분포에 의존한 소프트웨어 평균고장간격시간에 관한 모수 추정법 비교 연구

  • Kim, Hee Cheul (Namseoul Univ., Dept. of Industrial & Management Engineering) ;
  • Moon, Song Chul (Department of Computer Science, Namseoul University)
  • Received : 2017.03.02
  • Accepted : 2017.03.31
  • Published : 2017.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

Keywords

References

  1. Goel, A. L. and Okumoto, K, "Time-dependent fault detection rate model for software and other performance measures", IEEE Trans. Reliab., Vol. 28, No. 3, 1978, pp. 206-211.
  2. Gokhale, S. S. and Trivedi, K. S. A., "A time/structure based software reliability model", Annals of Software Engineering, Vol. 8, No. 1, 1999, pp. 85-121. https://doi.org/10.1023/A:1018923329647
  3. Kanoun, K. and Laprie, J. C., "Handbook of Software Reliability Engineering", R. Lyu, Editor, chapter Trend Analysis. McGraw- Hill New York, NY, 1996, pp. 401-437.
  4. Kim, H. C., Kim, J. B., and Moon, S. C., "A Comparative Study on Software Reliability Model for NHPP Intensity Function Following a Decreasing Pattern", Journal of Information Technology Applications and Management, Vol. 23, No. 4, 2016, pp. 117-125. https://doi.org/10.21219/JITAM.2016.23.4.117
  5. Kim, H.-C., "A Performance Analysis of Software Reliability Model using Lomax and Gompertz Distribution Property", Indian Journal of Science and Technology, Vol. 9, No. 20, 2016, pp. 1-6.
  6. Kim, H.-C., "The Property of Learning effect based on Delayed Software S-Shaped Reliability Model using Finite NHPP Software Cost Model", Indian Journal of Science and Technology, Vol. 8, No. 34, 2015, pp. 1-7.
  7. 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, Vol. 93, No. 10, 2008, pp. 1410-1421. https://doi.org/10.1016/j.ress.2007.11.004
  8. Lutfiah Ismail, A. T., "Testing the Performance of the Power Law Process Model Considering the Use of Regression Approach", International Journal of Software Engineering and Applications, Vol. 5, No. 5, 2014, pp. 35-46. https://doi.org/10.5121/ijsea.2014.5503
  9. Manton, K. G., Stallard, E., and Vaupel, J. W., "Alternative Models for the Heterogeneity of Mortality Risks Among the Aged", Journal of the American Statistical Association, Vol. 81, No. 395, 1986, pp. 635-644. https://doi.org/10.1080/01621459.1986.10478316
  10. Ross, S. M., "Introduction to Probability and Statistics for Engineers and Scientists", Academic Press, San Diego, USA, 2000, pp. 541-567.
  11. Sylwia, K. B., "Makeham's Generalized Distribution", Computational Methods in Science and Technology, Vol. 13, No. 2, 2007, pp. 113-120. https://doi.org/10.12921/cmst.2007.13.02.113-120
  12. Yang, T.-J., "The Comparative Study of NHPP Software Reliability Model Based on Log and Exponential Power Intensity Function", The Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol. 8, No. 6, 2015, pp. 445-452. https://doi.org/10.17661/jkiiect.2015.8.6.445
  13. Yoo, T.-H., "The Infinite NHPP Software Reliability Model based on Monotonic Intensity Function", Indian Journal of Science and Technology, Vol. 8, No. 14, 2015, pp. 1-7.