• Title/Summary/Keyword: Yamada-Ohba-Osaki 모형

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The Comparison of Parameter Estimation for Nonhomogeneous Poisson Process Software Reliability Model (NHPP 소프트웨어 신뢰도 모형에 대한 모수 추정 비교)

  • Kim, Hee-Cheul;Lee, Sang-Sik;Song, Young-Jae
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1269-1276
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    • 2004
  • The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.

The Study for NHPP Software Reliability Growth Model Based on Hyper-exponential Distribution (초지수분포(Hyper-exponential)를 이용한 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.7 no.1
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    • pp.45-53
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    • 2007
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the hyper-exponential distribution reliability model, which maked out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method. For model determination and selection, explored goodness of fit (the error sum of squares). The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution (shape 0.1 & scale 1) of Minitab (version 14) statistical package.

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The Study for NHPP Software Reliability Growth Model based on Exponentiated Exponential Distribution (지수화 지수 분포에 의존한 NHPP 소프트웨어 신뢰성장 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.5 s.43
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    • pp.9-18
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    • 2006
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

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The Comparative Study for Software Reliability Models Based on NHPP (NHPP에 기초한 소프트웨어 신뢰도 모형에 대한 비교연구)

  • Gan, Gwang-Hyeon;Kim, Hui-Cheol;Lee, Byeong-Su
    • The KIPS Transactions:PartD
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    • v.8D no.4
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    • pp.393-400
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    • 2001
  • This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

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The Study for NHPP Software Reliability Model based on Chi-Square Distribution (카이제곱 NHPP에 의한 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Society of Computer and Information
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    • v.11 no.1 s.39
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    • pp.45-53
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    • 2006
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

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The Study for NHPP Software Reliability Growth Model based on Burr Distribution (Burr 분포를 이용한 NHPP소프트웨어 신뢰성장모형에 관한 연구)

  • Kim, Hee-Cheul;Park, Jong-Goo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.3
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    • pp.514-522
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    • 2007
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this parer, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Burr distribution reliability model, which making out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing shape parameter of the Burr distribution was employed. This analysis of failure data compared with the Burr distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

The study for NHPP Software Reliability Model based on Kappa(2) distribution (Kappa(2) NHPP에 의한 소프트웨어 신뢰성 모형에 관한 연구)

  • Kim, Hee-Cheul
    • Journal of the Korea Computer Industry Society
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    • v.6 no.5
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    • pp.689-696
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    • 2005
  • Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

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