• 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.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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2311-2318
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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. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require Release times of a critical element of the software testing process : test coverage. This model called Enhanced non-homogeneous Poission process(ENHPP). In this paper, exponential coverage and S-shaped model was reviewed, proposes the Kappa coverage model, which make out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics and Kolmogorov distance, for the sake of efficient model, was employed. Numerical examples using real data set for the sake of proposing Kappa coverage model was employed. This analysis of failure data compared with the Kappaa coverage 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.325-330
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• 2018

This paper, following the shape parameters of the minimax distribution, describes the special form of the beta distribution, the Minimax distribution, as a function of the shape parameters for the software reliability model based on the non-homogeneous Poisson process. Characteristics and usefulness were discussed. As a result, the case of the shape parameter 1 of Minimax distribution than less than and greate in mean squared error is the smallest, in determination coefficient, appears to be high, the shape parameter 1 of Minimax distribution regard as an efficient model. The estimated determination coefficient of the proposed model is estimated to be more than 95%, which is a useful model in the field of software reliability. Through this study, software design and users can identify the software failure characteristics using mean square error, decision coefficient, and confidence interval can be used as a basic guideline.

• 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.