• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1741-1744
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• 2003

본 논문에서는 NHPP 에 근거한 N 버전 프로그래밍 시스템의 SRGM 을 제안한다. 비록 많은 연구 논문에서 NVP, 시스템 신뢰도에 대해서 연구노력을 기울여 왔지만 그들 대부분이 안정된 신뢰도에 대해서만 고려해 왔다. 테스트 및 디버깅 동안 결함이 발견되면 디버깅 노력은 결함을 제거하는데 집중된다. 소프트웨어가 너무 복잡하므로 이러한 결함을 성공적으로 제거한다는 것이 쉽지 않으며, 또 다른 새로운 결함이 소프트웨어에 도입될 수도 있다. 일반화된 NHPP 모델을 NVP 시스템에 적용하여 새로운 NVP-SRGM이 수립된다. 제어시스템에 대한 단순화된 소프트웨어 제어에서 이러한 새로운 소프트웨어 신뢰도 모델을 어떻게 적용하는지를 보여주고 있다. 소프트웨어 신뢰도평가에 s 신뢰도 구간을 준비하였다. 이 소프트웨어 신뢰도 모텔은 신뢰도를 평가하는데 쓰일 수가 있어서 NVP 시스템의 성능을 예측하는데 쓰일 수 있다. 일반적인 산업사회에 적용하여 상용화하기 위해서는 내결함 소프트웨어의 신뢰도를 정량화하기 위해 제안된 NVP-SRGM을 충분히 인증하는데 좀더 적용이 필요하다. NVP 신뢰도 성장 모델링을 하는 이러한 종류의 첫 모델로서 제안된 NVP-SRGM은 독립 신뢰도 모델의 단점을 극복하는데 쓰일 수 있다. 이는 독립적인 모델보다 더욱 더 정확하게 시스템 신뢰도를 예측할 수 있으며, 언제 테스트를 중단해야 하는가를 결정하는 데에도 쓰일 수 있으며, 이는 NVP 시스템 개발 수명주기 단계를 테스트 및 디버깅함에 있어서 핵심 질문사항이다.

• Convergence Security Journal
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• v.13 no.1
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• pp.3-10
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• 2013

In this paper, reliability software model considering fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the S-shaped distribution model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model was used. In a software failure data analysis considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of failure time data and reliability make out.

• 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.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.813-823
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• 2008

The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Convergence Security Journal
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• v.12 no.6
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• pp.85-92
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• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• Convergence Security Journal
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• v.7 no.3
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• pp.51-60
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• 2007

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.4
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• pp.460-466
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• 2018

With the development of information technology, the scale of computer software system is constantly expanding. Reliability and cost of software development have a great impact on software quality. In this study, based on the software failure interval time data, a comparative analysis was performed on the characteristics of the software development cost model based on the lifetime distribution following the Type-2 Gumbel and Erlang distribution in the NHPP model. As a result, the trends of the cost curves for the Go-Okumoto model and the proposed Erlang model and the Type-2 Gumble model both decreased in the initial stage and gradually increased in the latter half of the failure time. Also, Comparing the Erlang model with the Type-2 Gumble model, we found that the Erlang model is faster and more cost-effective at launch. Through this study, Software operators should remove possible defects from the testing phase rather than the operational phase to reduce defects after the software release date, it is expected to be able to study the prior information needed to understand the characteristic of software development cost.

• 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.

• 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.