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A Study on the Attribute Analysis of Software Reliability Model with Shape Parameter Change of Infinite Fault NHPP Lomax Life Distribution

무한고장 NHPP Lomax 수명분포의 형상모수 변화에 따른 소프트웨어 신뢰성 모형의 속성 분석에 관한 연구

  • Min, Kyung-il (Dept. of Public Health Administration, Namseoul University)
  • 민경일 (남서울대학교 보건행정학과)
  • Received : 2019.07.11
  • Accepted : 2019.08.20
  • Published : 2019.08.28

Abstract

In this study, the optimal shape parameter condition is presented after analyzing the attributes of the software reliability model according to the change of the shape parameter of Loma life distribution with infinite fault NHPP. In order to analyze the software failure phenomena, the parametric estimation method was applied to the Maximum Likelihood Estimation method, and the nonlinear equation was applied to the bisection method. As a result, it was found that when the attributes according to the change of the shape parameter are compared, the smaller the shape parameter is, the better the prediction ability of the true value, and reliability attributes are efficient. Through this study, it is expected that software developers can increase reliability by preliminarily grasping the type of software failure based on shape parameter, and can be used as basic information to improve the software reliability attributes.

본 연구에서는 무한고장 NHPP 로맥스 수명분포의 형상모수 변화에 따른 소프트웨어 신뢰성 모형의 속성을 새롭게 분석한 후 최적의 형상모수 조건을 제시하였다. 소프트웨어 고장현상을 분석하기 위하여 모수추정은 최우추정법을 사용하였고, 비선형 방정식의 계산은 이분법을 적용하였다. 그 결과, 형상모수(k)의 변화에 따른 속성을 비교하였을 때 형상모수가 작을 수록 참값에 대한 예측능력이 우수하고, 신뢰 속성이 효율적임을 알 수 있었다. 본 연구를 통하여, 소프트웨어 개발자들은 형상모수에 근거한 소프트웨어 고장형태를 사전에 파악함으로서 신뢰도를 성장시킬 수 가 있으며, 또한, 소프트웨어의 신뢰속성을 향상시키는데 필요한 기본정보로 활용할 수 있을 것으로 기대한다.

Keywords

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Fig. 1. Probability density function (λ=0.5)

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Fig. 2. Laplace Trend Test

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Fig. 3. Transition of Mean Square Error(MSE)

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Fig. 4. Transition of Intensity Function λ(t)

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Fig. 5. Pattern of Mean Value Function m(t)

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Fig. 6. Transition of Reliability Ȓ(t)

Table 1. Software Failure Time Data

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Table 2. Parameter estimation of the each model and MSE, R2

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