• Title/Summary/Keyword: 감마족 분포

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Analysis of Software Reliability Growth Model with Gamma Family Distribution (감마족 분포를 이용한 소프트웨어 신뢰 성장 모형의 분석)

  • Kan, Kwang-Hyun;Jang, Byeong-Ok;Kim, Hee-Cheul
    • Journal of IKEEE
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    • v.9 no.2 s.17
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    • pp.143-151
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    • 2005
  • Finite failure NHPP models proposed in the literature exhibit is either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. For the sake of proposing shape parameter of the Gamma family distribution, used the special pattern. Data set, where the underlying failure process could not be adequately described by the knowing models, which motivated the development of the Gamma or Weibull model and Gompertz model. Analysis of failure data set that led us to the Gamma or Weibull model and Gompertz model using arithmetic and Laplace trend tests, bias tests was presented in this Paper.

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Comparative Analysis on the Attributes of NHPP Software Development Cost Model Applying Gamma Family Distribution (감마족 분포을 적용한 NHPP 소프트웨어 개발비용 모형의 속성에 관한 비교 분석)

  • Hyo-Jeong Bae
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.867-876
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    • 2023
  • In this study, the attributes of the NHPP software development cost model applying the Gamma family distribution (Erlang, Log-Logistic, Rayleigh) were newly analyzed, and after comparing with the Goel-Okumoto basic model to verify the properties of the model, the optimal model was also presented based on this. To analyze software reliability, failure time data that occurred randomly during system operation was used, and the calculation of the parameters was solved using the maximum likelihood estimation. As a result of comprehensive evaluation through various attribute analysis (mean value function, development cost, optimal release time), it was confirmed that the Rayleigh model had the best performance. Through this study, the attributes of the software development cost model applying the Gamma family distribution, which has no previous research case, were newly identified. Also, basic design data could also be presented so that developers can efficiently utilize this research data at an early stage.

The Study of Software Optimal Release Using Sensitivity Analysis (민감도 분석을 이용한 소프트웨어 최적방출시기에 관한 연구)

  • Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.8 no.4
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    • pp.121-126
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    • 2008
  • It is of great practical interest to decide when to stop testing a software system in development phase and transfer it to the user. This decision problem called an optimal release policies. In this paper discussed to specify an optimal release policies. In this paper, propose an optimal release policies of the life distribution applied Erlang distribution of special pattern of Gamma distribution. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. From Sensitivity Analysis, make out estimating software optimal release time.

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A Study of Infinite Failure NHPP Software Reliability Growth Model base on Record Value Statistics with Gamma Family of Lifetime Distribution (수명분포가 감마족인 기록값 통계량에 기초한 무한고장 NHPP 소프트웨어 신뢰성장 모형에 관한 비교 연구)

  • Kim, Hee-Cheul;Sin, Hyun-Cheul
    • Convergence Security Journal
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    • v.6 no.3
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    • pp.145-153
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    • 2006
  • Infinite failure NHPP models for a record value satisfies mode proposed in the literature exhibit either monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, propose comparative study of software reliability model using Erlang distribution, Rayleigh and Gumbel distribution. Equations to estimate the parameters using maximum likelihood estimation of infinite failure NHPP model based on failure data collected in the form of interfailure times are developed. For the sake of proposing distribution, we used to the special pattern. Analysis of failure data set using arithmetic and Laplace trend tests, goodness-of-fit test, bias tests is presented.

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Bayesian Inference for Mixture Failure Model of Rayleigh and Erlang Pattern (RAYLEIGH와 ERLANG 추세를 가진 혼합 고장모형에 대한 베이지안 추론에 관한 연구)

  • 김희철;이승주
    • The Korean Journal of Applied Statistics
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    • v.13 no.2
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    • pp.505-514
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    • 2000
  • A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. For each observed failure epoch, we introduced mixture failure model of Rayleigh and Erlang(2) pattern. This data augmentation approach facilitates specification of the transitional measure in the Markov Chain. Gibbs steps are proposed to perform the Bayesian inference of such models. For model determination, we explored sum of relative error criterion that selects the best model. A numerical example with simulated data set is given.

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