• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.14-22
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• 1994

This paper proposes two Bayes estimators and their evaluation algorithms of the software reliability at the end testing stage in the Smith's Bayesian software reliability growth model under the data prior distribution BE(a, b), which is more general than uniform distribution, as a class of prior information. We consider both a squared-error loss function and the Harris loss function in the Bayesian estimation procedures. We also compare the MSE performances of the Bayes estimators and their algorithms of software reliability using computer simulations. And we conclude that the Bayes estimator of software reliability under the Harris loss function is more efficient than other estimators in terms of the MSE performances as a is larger and b is smaller, and that the Bayes estimators using the beta prior distribution as a conjugate prior is better than the Bayes estimators under the uniform prior distribution as a noninformative prior when a＞b.

• 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.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.444-447
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• 2006

We propose software reliability growth model, considering testing effort resource during testing stage of S/W, and compare the time dependent testing effort resource behavior in this paper. We develop the data technology method for the S/W reliability measure. We study in detail between the time elapse and reliability. Also, we determine the optimum release time which meets the target reliability. We decide optimum release time for each condition how the reliability is good before testing after development.

• Journal of Digital Convergence
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• v.19 no.8
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• pp.249-255
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• 2021

This study proposed a method for determining weights for the eight quality characteristics, such as functionality, reliability, usability, maintainability, portability, efficiency, security, and interoperability, which are suggested by international standards, focusing on software test reports. Currently, the test results for software quality evaluation apply the same weight to 8 quality characteristics to obtain the arithmetic average. Weights for 8 quality characteristics were applied using the results from text analysis, and weights were applied using the results of text analysis of test reports for two products. It was confirmed that the average of test reports according to the weighted quality characteristics was more efficient.

• 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.

• International Commerce and Information Review
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• v.2 no.1
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• pp.25-48
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• 2009

With the rapid growth of e-logistics in the global logistics industry, it is important to gain further insight into this growing segment of Chinese logistics industry. The current situation in China consists of many small and medium-sized logistics firms. Furthermore, e-logistics is still relatively undeveloped in the majority of the Chinese logistics companies and presently there are still many problems unresolved. This paper attempted to review the concepts and theoretical background of e-logistics systems from previous studies. After acknowledging the essential issues related to e-logistics systems, a research model based on the theory acceptance model was designed and tested. The key factors to the e-logistics system (reliability, maintainability, software, facility and transportation) were validated through the modeling and testing process. Included in the modelling and testing process are other related factors of e-logistics process, logistics information system and added value as dependent variables in this model. The results of this study confirm that the e-logistics Process is affected by transportation, while maintainability and software factors influence logistics information system. reliability, maintainability, facility and transportation are significant factors associated with added value. This research aimed to provide theoretical and practical contribution to Chinese logistics companies and to give some insights into e-logistics system as a whole. The paper also provided some useful theoretical implication and practical guidelines for the development of e-logistics system in the chinese logistics industry.

• International Commerce and Information Review
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• v.11 no.2
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• pp.3-26
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• 2009

With the rapid growth of e-logistics in the global logistics industry, it is important to gain further insight into this growing segment of Chinese logistics industry. The current situation in China consists of many small and medium-sized logistics firms. Furthermore, e-logistics is still relatively undeveloped in the majority of the Chinese logistics companies and presently there are still many problems unresolved. This paper attempted to review the concepts and theoretical background of e-logistics systems from previous studies. After acknowledging the essential issues related to e-logistics systems, a research model based on the theory acceptance model was designed and tested. The key factors to the e-logistics system (reliability, maintainability, software, facility and transportation) were validated through the modeling and testing process. Included in the modelling and testing process are other related factors of e-logistics process, logistics information system and added value as dependent variables in this model. The results of this study confirm that the e-logistics Process is affected by transportation, while maintainability and software factors influence logistics information system. reliability, maintainability, facility and transportation are significant factors associated with added value. This research aimed to provide theoretical and practical contribution to Chinese logistics companies and to give some insights into e-logistics system as a whole. The paper also provided some useful theoretical implication and practical guidelines for the development of e-logistics system in the chinese logistics industry.

• Convergence Security Journal
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• v.12 no.3
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• pp.115-121
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• 2012

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.585-589
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• 2002

본 연구에서는 소프트웨어의 출시 이후 주기적인 보수(periodic maintenance)를 고려한 출시 시기 결정 방법을 제시하였다. 출시시기 결정방법에 관한 연구는 소프트웨어의 신뢰성 확보, 사용자 편의성 등에 관한 연구와 더불어 중요한 연구 분야로 여겨지는 분야이다. 일반 적으로 소프트웨어는 출시 이후에도 패치(patch), 서비스팩(service pack)등을 통해 지속적인 보수가 이루어지기 때문에, 출시 이후의 보수를 고려하여 출시시기를 결정하는 방법론이 필요하다. 이를 위해, 출시 이후의 보수정책을 반영한 소프트웨어 신뢰성 성장 모형(software reliability growth model)을 도출하였다. 위 모형을 기반으로 하여 비용과 신뢰성에 근거한 소프트웨어 출시 시점을 결정해 보았다. 제시된 모형의 타당성을 검증하기 위해 예제를 통해 기존의 논문에서 제시되었던 결과들과 비교분석을 해 보았다. 본 연구의 결과는 기존 연구에서 고려되지 않았던 보수 정책을 고려함으로써, 보다 현실에 가까운 모형을 제시하였다는 점에서 의의를 찾을 수 있고, 출시 후 보수 시점, 보수 정책 등의 결정에도 기여할 수 있을 것이다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.12
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• pp.3821-3828
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• 2000

Many software projects collect grouped failure data (failures in some failure interval or in variable time interval) rather than individual failure times or failure count data during the testing or operational phase. This paper presents the neural network (NN) modeling that is dble to predict cumulative failures in the variable future time for grouped failure data. ANN's predictive ability can be affected by what it learns and in its ledming sequence. Eleven training regimes that represents the input-output of NN are considered. The best training regimes dre selected rJdsed on the next' step dvemge reldtive prediction error (AE) and normalized AE (NAE). The suggested NN models are compared with other well-known KN models and statistical software reliability growth models (SHGlvls) in order to evaluate performance, Experimental results show that the NN model with variable time interval information is necessary in order to predict cumulative failures in the variable future time interval.