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

한국전자통신학회 (Korea Institute of Electronic Communication Science)
권호 표지
DOI QR코드

DOI QR Code

Inverse-type 수명분포에 근거한 유한고장 NHPP 소프트웨어 개발비용 모형의 성능에 관한 비교 연구

Comparative Study on the Performance of Finite Failure NHPP Software Development Cost Model Based on Inverse-type Life Distribution

  • 박승규 (남서울대학교 전자공학과)
  • 투고 : 2023.08.27
  • 심사 : 2023.10.17
  • 발행 : 2023.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구에서는 신뢰성 연구에 적합하다고 알려진 Inverse-type(: Inverse-Exponential, Inverse-Rayleigh) 수명분포를 유한고장 NHPP(: Nonhomogeneous Poisson Process) 기반의 소프트웨어 개발비용 모형에 적용한 후, 성능을 결정하는 속성을 분석하였다. 또한, 모형의 효율성을 평가하기 위해 Goel-Okumoto 기본 모형과 함께 비교하였다. 고장 시간 데이터를 이용하여 모형의 성능을 분석하였고, 모수의 계산은 MLE(: Maximum Likelihood Estimation)를 적용하였다. 결론적으로, 첫째, 개발비용을 결정하는 m(t)를 분석한 결과, Inverse-Exponential 모형이 참값에 대한 오차가 적어 효율적이었다. 둘째, 개발비용과 함께 방출시간을 분석한 결과 Inverse-Rayleigh 모형이 가장 좋은 것으로 확인되었다. 셋째, 제안된 모형의 속성(m(t), 비용, 방출시간)을 종합적으로 평가한 결과, Inverse-Rayleigh 모형의 성능이 가장 우수하였다. 따라서 소프트웨어 개발자가 초기 프로세스에서 본 연구 데이터를 효율적으로 활용할 수 있다면, 비용에 영향을 미치는 속성들을 사전에 탐색하고 분석할 수 있을 것이다.

In this study, the Inverse-type (: Inverse-Exponential, Inverse-Rayleigh) life distribution, which is known to be suitable for reliability research, was applied to a software development cost model based on finite failure NHPP(: Nonhomogeneous Poisson Process), and then the attributes that determine the model's performance were analyzed. Additionally, to evaluate the efficiency of the model, it was compared with the Goel-Okumoto basic model. The performance of the model was analyzed using failure time data, and MLE (: Maximum Likelihood Estimation) was applied to calculate the parameters. In conclusion, first, as a result of analyzing m(t), which determines the development cost, the Inverse-Exponential model was efficient due to its small error in the true value. Second, as a result of analyzing the release time along with the development cost, the Inverse-Rayleigh model was confirmed to be the best. Third, as a result of comprehensive evaluation of the attributes (m(t), cost, and release time) of the proposed model, the Inverse-Rayleigh model had the best performance. Therefore, if software developers can effectively utilize this research data in the early process, they will be able to proactively explore and analyze attributes that affect cost.

키워드

과제정보

이 논문은 2022년도 남서울대학교 학술연구비 지원에 의해 연구되었음.

참고문헌

  1. R. Lai, and M. Trivedi, "A Detailed Study of NHPP Software reliability models," Journal of Software, vol. 7, no. 6, 2012, pp. 1296-1306. https://doi.org/10.4304/jsw.7.6.1296-1306
  2. S, Chatterjee, J. Singh and A. Roy & A. Shukla, "NHPP-Based Software Reliability Growth Modeling and Optimal Release Policy for N-Version Programming System with Increasing Fault Detection Rate under Imperfect Debugging," Proceedings of the National Academy of Sciences, India Section A, vol. 90, no.1, 2020, pp. 11-26.
  3. H. Pham and X. Zhang "NHPP Software Reliability and Cost Models with Testing Coverage," European Journal of Operational Research, vol. 145, 2003, pp. 443-454. https://doi.org/10.1016/S0377-2217(02)00181-9
  4. R. Shenbagam and Y. Sarada, "On a Cost and Availability Analysis for Software System Via Phase Type Non-homogeneous Poisson Process," Communications in Statistics-Theory and Methods, 2023, pp. 1-22.
  5. J. Kim and Y. Yang, "Comparative Study on the Cost Analysis of Software Development Model Applicable to System Solutions Based on Gamma Family Distribution," International Journal of Electrical Engineering and Technology, vol 12, Issue. 9, 2021, pp. 43-54. https://doi.org/10.34218/IJEET.12.9.2021.005
  6. H. Kim, "A Comparative Study on the Cost of Software Development Model Based on Burr-Hatke-Exponential Distribution," International Journal of Engineering Research and Technology, vol. 12, no.11, 2019, pp. 2036-2040.
  7. H. Kim and K. Kim, "Software Development Cost Model based on NHPP Gompertz Distribution," Indian Journal of Science and Technology, vol. 8, no. 12, 2015, pp. 1-5. https://doi.org/10.17485/ijst/2015/v8i12/68332
  8. T. Yang, "Performance Analysis on the Reliability Attributes of NHPP Software Reliability Model Applying Exponential and Inverse-Exponential Lifetime Distribution," Journal of Theoretical and Applied Information Technology, vol. 100, no. 22, 2022, pp. 6645-6656.
  9. H. Bae, "Performance Attributes Analysis of Software Development Cost Model with Gamma Family Distribution Characteristics," Journal of Theoretical and Applied Information Technology, vol. 101, no. 10, 2023, pp. 3816-3826.
  10. T. Yang, "Comparative Analysis on the Reliability Performance of NHPP Software Reliability Model Applying Exponential-Type Lifetime Distribution," International Journal of Performability Engineering. vol. 18, no. 10, 2022, pp. 679-689. https://doi.org/10.23940/ijpe.22.10.p1.679-689
  11. T. Yang, "Comparative Study on the Performance Evaluation of Infinite Failure NHPP Software Reliability Model with Log-Type Distribution Property," ARPN Journal of Engineering and Applied Sciences. vol. 17, no. 11, 2022, pp. 1209-1218.
  12. Y. Zhang and K. Wu, "Software Cost Model Considering Reliability and Time of Software in Use," Journal of Convergence Information Technology, vol. 7, no. 13, 2012, pp. 135-142. https://doi.org/10.4156/jcit.vol7.issue13.16
  13. T. Yang and J. Park, "A Comparative Study of the Software NHPP Based on Weibull Extension Distribution and Flexible Weibull Extension Distribution," International Journal of Soft Computing. vol. 11, no. 4, 2016. pp. 276-281.
  14. Y. Hayakawa and G. Telfar, "Mixed Poisson-type Process with Application in Software Reliability," Mathematical and Computer Modelling. vol. 31, no. 10-12, 2000, pp. 151-156. https://doi.org/10.1016/S0895-7177(00)00082-0
  15. C. Lee. and H. Baek, "A Study on The Need for AI Literacy According to The Development of Artificial Intelligence Chatbot" The Journal of The Korea Institute of Electronic Communication Sciences, vol. 18, no. 3, 2023. pp. 421-426.
  16. Y. Ju, J. Kim and E. Kim, "Development of External Expansion Devices and Convergence Contents for Future Education based on Software Teaching Tools," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 16, no. 6, 2021, pp.1317-1322.
  17. S. Lee, "A Routing Algorithm based on Deep Reinforcement Learning in SDN," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 16, no. 6, 2021. pp. 1153-1160.
  18. Y. Song, Y. Lee and Y. Goo, "A Study on the Weapon System Software Reliability Testing for the Joint Tactical Data Link System Project Case," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 17, no. 4, 2022. pp. 663-670.
  19. J. Seo, "A Study on Image Classification using Deep Learning-Based Transfer Learning," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 18, no. 3, 2023. pp. 413-420.
  20. S. Park, "Comparative Analysis on the Performance of NHPP Software Reliability Model with Exponential Distribution Characteristics" The Journal of The Korea Institute of Electronic Communication Sciences, vol. 17, no. 4, 2022. pp. 641-648.