• 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.

• 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.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.25-32
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• 2017

For repairable software systems, the Mean Time Between Failure (MTBF) is used as a measure of software system stability. Therefore, the evaluation of software reliability requirements or reliability characteristics can be applied MTBF. In this paper, we want to compare MTBF in terms of parameter estimation using Makeham life distribution. The parameter estimates used the least square method which is regression analyzer method and the maximum likelihood method. As a result, the MTBF using the least square method shows a non-decreased pattern and case of the maximum likelihood method shows a non-increased form as the failure time increases. In comparison with the observed MTBF, MTBF using the maximum likelihood estimation is smallerd about difference of interval than the least square estimation which is regression analyzer method. Thus, In terms of MTBF, the maximum likelihood estimation has efficient than the regression analyzer method. In terms of coefficient of determination, the mean square error and mean error of prediction, the maximum likelihood method can be judged as an efficient method.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.885-892
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• 2004

Weibull distribution Iincluding Rayleigh and Exponential distribution is a typical model to estimate the effort distribution which is committed to the software testing phase. This model does not represent standpoint that many efforts are committed actually at the test beginning point. Moreover, it does not properly represent the various distribution form of actual test effort. To solve these problems, this paper proposes the Sigmoid model. The sigmoid function to be applicable in neural network transformed into the function which properly represents the test effort of software in the model. The model was verified to the six test effort data which were got from actual software projects which have various distribution form and verified the suitability. The Sigmoid model nay be selected by the alternative of Weibull model to estimate software test effort because it is superior than the Weibull model.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.278-284
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• 2016

Software reliability in the software development process is an important issue. In infinite failure NHPP software reliability models, the fault occurrence rates may have constant, monotonic increasing or monotonic decreasing pattern. In this paper, infinite failures NHPP models that the situation was reflected for the fault occurs in the repair time, were presented about comparing property. Commonly, the software model of the infinite failures using the linear hazard rate distribution software reliability based on intercept parameter was used in business economics and actuarial modeling, was presented for comparison problem. The result is that a relatively large intercept parameter was appeared effectively form. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination. The linear hazard rate distribution model is also efficient in terms of reliability because it (the coefficient of determination is 90% or more) in the field of the conventional model can be used as an alternative model could be confirmed. From this paper, the software developers have to consider intercept parameter of life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.507-509
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• 2000

This study developed the window based power flow analysis software for distribution system. This system was developed by using Visual C++ 6.0 in Microsoft Windows 98 environment; therefore, it utilized many advantages of window based programming for providing user-friendly interface. The backward/forward sweep algorithm is implemented in this software for power flow analysis. Especially, this software includes the newly developed classes of complex function, matrix function, and power flow calculation procedure, so it has high flexibility for enhancement and modifications.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.405-414
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• 2012

In this paper, we propose a reliability estimation method for DI&C systems. At the system level, a fault tree model is suggested and Boolean algebra is used to obtain the minimal cut sets. At the component level, an exponential distribution is used to model hardware failures, and Bayesian estimation is suggested to estimate the failure rate. Additionally, a binomial distribution is used to model software failures, and a recently developed software reliability estimation method is suggested to estimate the software failure rate. The overall system reliability is then estimated based on minimal cut sets, hardware failure rates and software failure rates.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.141-147
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• 2016

NHPP software reliability models for failure analysis can have, in the literature, exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, infinite failures NHPP models that repairing software failure point in time reflects the situation, was presented for comparing property. Commonly used in the field of software reliability based on Flexible Weibull extension distribution software reliability of infinite failures was presented for comparison problem. The result is that a relatively small shaping parameter was effectively. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination.. In this research, software developers to identify software failure property follows shape parameter, some extent be able to help is considered.