변형된 강도함수를 적용한 소프트웨어 신뢰모형의 신뢰성능 비교 평가에 관한 연구 = A Study on the Reliability Performance Evaluation of Software Reliability Model Using Modified Intensity Function

다국어 초록 (Multilingual Abstract)

In this study, we was compared the reliability performance of the software reliability model, which applied the Goel-Okumoto model developed using the exponential distribution, to the logarithmic function modifying the intensity function and the Rayleigh form. As a result, the log-type model is relatively smaller in the mean squared error compared to the Rayleigh model and the Goel-Okumoto model. The logarithmic model is more efficient because of the determination coefficient is relatively higher than the Goel-Okumoto model. The estimated determination coefficient of the proposed model was estimated to be more than 80% which is a useful model in the field of software reliability. Reliability has been shown to be relatively higher in the log-type model than the Rayleigh model and the Goel-Okumoto model as the mission time has elapsed. Through this study, software designer and users can identify the software failure characteristics using mean square error, decision coefficient. The confidence interval can be used as a basic guideline when applying the intensity function that reflects the characteristics of the lifetime distribution.

참고문헌 (Reference)

1 김희철, "로그 및 지수형 결함 발생률에 따른 소프트웨어 신뢰성 모형에 관한 신뢰도 성능분석 연구" 한국정보전자통신기술학회 9 (9): 306-311, 2016

2 "https://www.r-project.org/"

3 Goel, A. L., "Time-dependent fault detection rate model for software and other performance measures" 28 : 206-211, 1978

4 Yamada, S., "Software reliability growth modeling : models and applications" 11 (11): 1431-1437, 1985

5 Huang, C. Y., "Performance analysis of software reliability growth models with testing-effort and change-point" 76 (76): 181-194, 2005

6 Hayakawa, Y., "Mixed poissontype processes with application in software are reliability" 31 : 151-156, 2000

7 Kuei-Chen, C., "A study of software reliability growth from the perspective of learning effects" 93 (93): 1410-1421, 2008

8 Teng, X., "A new methodology for predicting software reliability in the random field environments" 55 (55): 458-468, 2006

9 Song, K. Y., "A Software Reliability Model with a Weibull Fault Detection Rate Function Subject to Operating Environments" 7 (7): 1-16, 2007

10 Yoo, T. H., "A Performance Valuation for NHPP Software Reliability Model depend on Weibull-Type Distribution" 118 (118): 1021-1033, 2018

11 Kim, H. -C., "A Performance Analysis of Software Reliability Model using Lomax and Gompertz Distribution Property" 9 (9): 1-6, 2016

12 Chatterjee, S., "A NHPP based software reliability model and optimal release policy with logistic-exponential test coverage under imperfect debugging" 5 (5): 399-406, 2014

13 Kim, H. -C., "A Comparative Study on Software Reliability Models with Shape Parameter of Type-2 Gumble Life Distribution" 12 (12): 351-354, 2017

14 Kim, H. -C., "A Comparative Study for Statistical Process Control of Software Reliability Model Base on Finite and Infinite NHPP Using Rayleigh Distribution" 11 (11): 165-171, 2016