• Convergence Security Journal
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• v.11 no.3
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• pp.19-24
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• 2011

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 offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, time series analys is used in the simple moving average and weighted moving averages, exponential smoothing method for predict the future failure times, Empirical analysis used interval failure time for the prediction of this model. Model selection using the mean square error was presented for effective comparison.

• 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 Information Science Society Conference
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• 1999.10a
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• pp.614-616
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• 1999

신뢰도 높은 소프트웨어 개발의 필요성은 전혀 새로운 것이 아니다. 요즘 들어, 소프트웨어의 크기와 복잡도가 증가함으로 인해 소프트웨어의 결함 때문에 발생하는 시스템 고장이 전체 시스템 고장에서 많은 비중을 차지하고 있다. 고 신뢰도를 요구하는 시스템의 소프트웨어는 복구블록, 분산 복구블록, N-버전 프로그래밍, N 자기검사 프로그래밍과 같은 소프트웨어 결함허용 기법들을 사용하고 있다. 이러한 소프트웨어 결함허용 기법들에 대한 연구와 함께 소프트웨어 결함허용 기법들의 의존도 측정에 관한 연구 또한 매우 중요하다. 이에 본 논문에서는 마르코프 모델을 사용해서 소프트웨어 결함허용 기법들의 보다 자세한 신뢰도 모델링과 가용도, 안전도 등에 관한 모델링을 제시한다. 제안된 모델 분석 결과 같은 수의 대체블록이 있을 때는 분산 복구블록, 복구 블록, N 자기검사 프로그래밍, N-버전 프로그래밍 순으로 의존도가 높음을 알 수 있다. 또한 소프트웨어 결함허용 기법들의 신뢰도민감성 분석에서는 복구블록과 분산 복구블록인 경우는 적응검사의 결함발생율에, N-버전 프로그래밍인 경우는 프로그램 버전의 결함발생율에 더 민감한 영향을 받는 것을 알 수 있다.

• Convergence Security Journal
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• v.10 no.1
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• pp.55-61
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• 2010

It is of great practical interest to deciding 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, because of the possibility of introducing new faults when correcting or modifying the software, we were researched release comparative policies which based on infinite failure NHPP model and types of interval failure times. The policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement can optimal software release times. In a numerical example, applied data which were patterns, if intensity function constant or increasing, decreasing, estimated software optimal release time.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.133-140
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• 2016

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, we were proposed the reliability model with the exponential and inverse exponential distribution, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, were employed. Analysis of failure, using real data set for the sake of proposing the exponential and inverse exponential distribution, was employed. This analysis of failure data compared with the exponential and inverse exponential distribution property. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the inverse exponential distribution model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.445-452
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• 2015

Software reliability in the software development process is an important issue. Software process improvement helps in finishing with reliable software product. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the reliability model with log and power intensity function (log linear, log power and exponential power), which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination($R^2$), for the sake of efficient model, was employed. Analysis of failure, using real data set for the sake of proposing log and power intensity function, was employed. This analysis of failure data compared with log and power intensity function. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the log type model is also efficient in terms of reliability because it (the coefficient of determination is 70% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can be able to help.

• The Transactions of the Korea Information Processing Society
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• v.5 no.5
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• pp.1225-1233
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• 1998

An important issue for software developers is to determine when to stop testing the software system and release it to users. Generally the release time is specified by the number of detected faults or the testing time needed to meet the reliability requirement. Software reliability directly depends on the number of remaining or corrected faults. All the detected faults are not always corrected under imperfect debugging environment. We therefore need a new approach to software release policy for imperfect debugging. This paper suggests a software release policy, which guarantees that the reliability requirement has been achieved. The suggested policy is then implemented and illustrated for specific SRGMs.

• ETRI Journal
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• v.14 no.1
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• pp.66-75
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• 1992

본고에서는 TDX-1A 시스팀의 운용 데이터를 신뢰도 측면에서 분석하여, 시스팀이 가지는 신뢰도 분포 특성과 고장 현황 구성을 살펴보았다. 또한 하드웨어 신뢰도만 예측될 수 있는 시스팀에서 예측하기 어려운 하드웨어 외적 요인에 의한 고장이 시스팀의 신뢰도에서 차지하는 부분을 추정함으로써 하드웨어 고장과 소프트웨어 및 운용중 에러에 의한 고장을 감안한 시스팀 신뢰도 예측이 가능하도록 하였다.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.437-441
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• 2004

As the development of networks and computer systems, users want various services. To meet user's various needs, new technologies is developed and a software streaming technology, uses software with streaming technology, is newly coming out. If network trouble occurs, the software is not available because the streaming server can't send the binary code that software needs to be executed in the streaming service based on network environment. In this paper, we propose the management technology of software binary code in client that managing the binary codes classfied by the function kept in the local storage device, provides the service continuously after the network trouble with the given binary code previously not the binary code from the server.