• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.409-411
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• 2001

본 논문에서는 소프트웨어 테스트 단계중에 발생되는 테스트노력 소요량을 고려한 소프트웨어 신뢰도 성장 모델을 제시하여 시간종속적인 테스트 노력소요량 동태를 일정 테스트 노력일 때와 웨이블 테스트 노력일 때를 비교하여 연구한다. 테스트 단계중에 소요되는 테스트노력의 양에 대한 결함 검출비를 현재의 절함 내용에 비례하는 것으로 가정하여 모델을 NHPP로 공식화하되, 이 모델을 이용하여 소프트웨어 신뢰도 척도에 대한 데이터 분식기법을 개발한다. 테스트 시간의 경과와 신뢰도와의 관계를 연구한다. 목표신뢰도를 만족시키는 최적발행시각을 정한다.

• Journal of Digital Convergence
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• v.11 no.12
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• pp.319-326
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• 2013

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. 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. 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). Statistical process control (SPC) can monitor the forecasting of software failure and thereby 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 logarithmic hazard learning effects property.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.6
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• pp.566-572
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• 2016

Software Reliability implemented in software development is one of the most important issues. In finite failure NHPP software reliability models for software failure analysis, the hazard function that means a failure rate may have constant independently for failure time, non-increasing or non-decreasing pattern. In this study, software development cost analysis considering the variable shape parameter of Erlang distribution as the failure life distribution in the software product testing process was studied. The software failure model was applied finite failure Non-Homogeneous Poisson Procedure and the parameters approximation using maximum likelihood estimation was accompanied. Thus, this paper was presented comparative analysis by applying a software failure time data to the software, considering the shape parameter of Erlang distribution for development cost model analysis. When compared to the cost curve in accordance with the shape parameter, the model of smaller shape can be seen that the optimal software release time delay and more cost. Through this study, it is thought that it can serve as a preliminary information which can basically help the software developers to search for development cost according to software shape parameters.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2060-2071
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• 1999

The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.835-842
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• 2001

We propose a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase. The time-dependent behavior of testing effort expenditures is described by a Weibull curve. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, we discuss the relations between testing time and reliability and between duration following failure fixing and reliability are studied in this paper. The release time making the testing cost to be minimum is determined through studying the cost for each condition. Also, the release time is determined depending on the conditions of the specified reliability. The optimum release time is determined by simultaneously studying optimum release time issue that determines both the cost related time and the specified reliability related time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.1-9
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• 2008

The Logistic cone is studied as a most desirable for the software testing effort. Assuming that the error detection rate to the amount of testing effort spent during the testing phase is proportional to the current error content, a software-reliability growth model is formulated by a nonhomogeneous Poisson process. Using this model the method of data analysis for software reliability measurement is developed. After defining a software reliability, This paper discusses the relations between testing time and reliability and between duration following failure fixing and reliability are studied SRGM in several literatures has used the exponential curve, Railleigh curve or Weibull cure as an amount of testing effort during software testing phase. However, it might not be appropriate to represent the consumption curve for testing effort by one of already proposed curves in some software development environments. Therefore, this paper shows that a logistic testing- effort function can be adequately expressed as a software development/testing effort curve and that it gives a good predictive capability based on real failure data.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.489-498
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• 2012

Most of the software reliability models are based on black box approach and these models consider the entire software system as a single unit. Present day software development process has changed a lot. In present scenario these models may not give better results. To overcome this problem an improved additive model has been proposed in this paper, to estimate the reliability of software with modular structure. Also the concept of imperfect debugging has been also considered. A maximum likelihood estimation technique has been used for estimating the model parameters. Comparison has been made with an existing model. ${\chi}^2$ goodness of fit has been used for model fitting. The proposed model has been validated using real data.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1109-1112
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• 2005

The software reliability is defined, and not only the relations between testing time and reliability, but also the relation between duration following failure fixing and reliability are studied in this paper. The release time making the testing cost to be minimum is determined through evaluating the cost for each condition. Also, the release time is determined depending on the conditions of the first reliability, considering the specified reliability. The optimum release time is determined by simultaneously studying two optimum release time issues that determine both the cost related time and the specified reliability related time. And, each condition and limitation are studied. The trend of the optimum time is also examined.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.697-704
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• 2005

Computer software has gradually become an indispensable elements in many aspects of our daily lives and an important factor in numerous systems. In recent years, it is not unusual that the software cost is more than the hardware cost in many situations. In addition to the costs of developing software, the repair cost resulting from the software failures are even more significant. In this paper, a cost model with warranty cost, time to remove each fault detected in the software system, and delivery delay cost is developed. We use a software reliability model based on non-homogeneous Poisson process (NHPP). We discuss the optimal release policies to minimize the expected total software cost. Numerical examples are provided to illustrate the results.