The Journal of the Korea institute of electronic communication sciences (한국전자통신학회논문지)

Korea Institute of Electronic Communication Science (한국전자통신학회)
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Comparative Analysis on the Performance of NHPP Software Reliability Model with Exponential Distribution Characteristics

지수분포 특성을 갖는 NHPP 소프트웨어 신뢰성 모형의 성능 비교 분석

  • 박승규 (남서울대학교 전자공학과)
  • Received : 2022.06.11
  • Accepted : 2022.08.17
  • Published : 2022.08.31
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Abstract

In this study, the performance of the NHPP software reliability model with exponential distribution (Exponential Basic, Inverse Exponential, Lindley, Rayleigh) characteristics was comparatively analyzed, and based on this, the optimal reliability model was also presented. To analyze the software failure phenomenon, the failure time data collected during system operation was used, and the parameter estimation was solved by applying the maximum likelihood estimation method (MLE). Through various comparative analysis (mean square error analysis, true value predictive power analysis of average value function, strength function evaluation, and reliability evaluation applied with mission time), it was found that the Lindley model was an efficient model with the best performance. Through this study, the reliability performance of the distribution with the characteristic of the exponential form, which has no existing research case, was newly identified, and through this, basic design data that software developers could use in the initial stage can be presented.

본 연구에서는 지수 형태의 분포(Exponential Basic, Inverse Exponential, Lindley, Rayleigh) 특성을 갖는 NHPP 소프트웨어 신뢰성 모형의 성능을 비교 분석하였고, 이를 근거로 최적의 신뢰성 모형도 함께 제시하였다. 소프트웨어 고장 현상을 분석하기 위하여 시스템 운영 중 수집된 고장 시간 데이터를 사용하였고, 모수 추정은 최우 추정 법을 적용하여 해결하였다. 다양한 비교 분석(평균제곱오차(MSE) 분석, 평균값 함수의 참값 예측력 분석, 강도 함수의 평가, 임무 시간을 적용한 신뢰도를 평가)을 통하여 Lindley 모형이 가장 우수한 성능을 가진 효율적인 모형임을 알 수 있었다. 본 연구를 통하여 기존 연구사례가 없는 지수 형태의 특성을 갖는 분포의 신뢰도 성능을 새롭게 파악하였고, 이를 통하여 소프트웨어 개발자들이 초기 단계에서 활용할 수 있는 기본적인 설계 데이터를 제시할 수 있었다.

Keywords

Acknowledgement

이 논문은 2021년도 남서울대학교 학술연구비 지원에 의해 연구되었음.

References

  1. K. Y. Song, I. H. Chang, H. Pham, "A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments," Applied Science, vol. 7, no. 983, pp.1-16, 2017.
  2. H. Pham, "Distribution Function and its Application in Software Reliability," International Journal of Performability Engineering, vol. 15, no. 5, pp. 1306-1313. 2019.
  3. X. Xiao, T. dohi "On the Role of Weibull-type Distribution in NHPP-based Software Reliability Modelling," International Journal of Performability Engineering, vol. 9, Issue. 2, pp.123-132, 2013.
  4. C. Y. Huang, "Performance analysis of software reliability growth models with testing-effort and change-point," Journal of Systems and Software, vol.76, no.2, pp.181-194, 2005. https://doi.org/10.1016/j.jss.2004.04.024
  5. H. C. Kim, "The Comparative Study for Statistical Process Control of Software Reliability Model on Finite and Infinite NHPP using Rayleigh Distribution," International Journal of Soft Computing, vol. 11, no. 3, pp. 165-171. 2016.
  6. T. J. Yang, "A study on the Reliability Performance analysis of finite failure NHPP software reliability model based on Weibull life distribution," International Journal of Engineering Research and Technology, vol. 12, no. 11, pp.1890-1896. 2019.
  7. T. J. Yang, "Comparative study on the attributes analysis of software development cost model based on exponential-type lifetime distribution," International Journal of Emerging Technology and Advanced Engineering, vol. 11, no. 10, pp. 166-176, 2021. https://doi.org/10.46338/ijetae1021_20
  8. T. J. Yang, "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 Commmunication Technology, vol.8, no.6, pp.445-452, 2015. https://doi.org/10.17661/jkiiect.2015.8.6.445
  9. Ye Zhang, and Kaigui Wu, "Software Cost Model Considering Reliability and Time of Software in Use," Journal of Convergence Information Technology, vol.7, no.13, pp.135-142, 2012. https://doi.org/10.4156/jcit.vol7.issue13.16
  10. T. J. Yang, "A Comparative Study on Reliability Attributes of Software Reliability Model Based on Type-2 Gumbel and Erlang Life Distribution," ARPN Journal of Engineering and Applied Science, vol. 14, no. 10, pp. 3366-3370. 2019. https://doi.org/10.36478/jeasci.2019.3366.3370
  11. H.C. Kim, "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, pp. 1-7, 2015.
  12. H. J. Jung, "A proposal of Software Quality Measurement Model and Testcase on the basis of ISO/IEC 25," The Journal of KIIT, vol. 9, no. 10, pp. 197-205, 2011.
  13. Y. Hayakawa, G. Telfar "Mixed poisson-type processes with application in software are reliability," Mathematical and Computer Modelling, vol. 31, pp.151-156, 2000. https://doi.org/10.1016/S0895-7177(00)00082-0
  14. E. K, Kim, "Development of a multi-tool carving machine and a machine control software," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 14, Issue. 4, pp. 755-760, 2019. https://doi.org/10.13067/JKIECS.2019.14.4.755
  15. S. U. Lee and M, B, Choi, "An Establishment of the Process System for Software Requirements Engineering," The Journal of IIBC, vol. 14, no. 1, pp. 37-49, 2014. DOI : http://dx.doi.org/10.7236/JIIBC.2014.14.1.37
  16. M. H. Cho, "A Study on the Direction of Modeling Techniques for the Development of Large Scale Software," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 15, Issue. 1, pp. 167-172, 2020. https://doi.org/10.13067/JKIECS.2020.15.1.167
  17. E. K, Kim, "Development of Software Education Products Based on Physical Computing," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 14, Issue. 3, pp. 595-600, 2019. https://doi.org/10.13067/JKIECS.2019.14.3.595
  18. H. C. Kim and H. K, Park, "The Comparative Study of Software Optimal Release Time Based on Weibull Distribution Property," Journal of the Korea Academia-Industrial cooperation Society, vol. 10, Issue. 8, pp. 1903-1901, 2009. DOI : https://doi.org/10.5762/KAIS.2009.10.8.1903