• 한국산학기술학회논문지
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• 제10권8호
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• pp.1903-1910
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• 2009

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구하였다. 인도시기에 관한 모형은 무한 고장수에 의존하는 비동질적인 포아송 과정을 적용하였다. 이러한 포아송 과정은 소프트웨어의 결함을 제거하거나 수정 작업 중에도 새로운 결함이 발생될 가능성을 반영하는 모형이다. 고장발생 수명분포는 여러 분포들을 적합시키는데 효율적인 특성을 가진 와이블분포를 이용하였다. 따라서 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화시키는 방출시간이 최적 소프트웨어 방출 정책이 된다. 본 논문의 수치적인 예에서는 고장 간격 시간 자료를 적용하고 모수추정 방법은 최우추정법과 추세분석을 통하여 자료의 효율성을 입증한 후 최적 방출시기를 추정하였다.

• 대한수학회지
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• 제52권3호
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• pp.447-467
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• 2015

In this paper, we consider a multi-risk model based on the policy entrance process with n independent policies. For each policy, the entrance process of the customer is a non-homogeneous Poisson process, and the claim process is a renewal process. The loss process of the single-risk model is a random sum of stochastic processes, and the actual individual claim sizes are described as extended upper negatively dependent (EUND) structure with heavy tails. We derive precise large deviations for the loss process of the multi-risk model after giving the precise large deviations of the single-risk model. Our results extend and improve the existing results in significant ways.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제10권2호
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• pp.41-47
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• 2006

The Renewal process and the Non-homogeneous Poisson process (NHPP) process are probably the most popular models for describing the failure pattern of repairable systems. But both these models are based on too restrictive assumptions on the effect of the repair action. For these reasons, several authors have recently proposed point process models which incorporate both renewal type behavior and time trend. One of these models is the Modulated Power Law Process (MPLP). The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose Bayes estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model. Numerical examples illustrate the estimation procedure.

• 디지털산업정보학회논문지
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• 제8권4호
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• pp.25-34
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• 2012

In this study, in the process of testing before the release of the software products designed, software testing manager in advance should be aware of the testing-information. Therefore, the effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and applied property of learning effect based on truncated time and delayed S-shaped software reliability. 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 autonomous errors-detected factor that is generally efficient model can be confirmed. This paper, a failure data analysis was performed, using time between failures, according to the small sample and large sample sizes. The parameter estimation was carried out using maximum likelihood estimation method. Model selection was performed using the mean square error and coefficient of determination, after the data efficiency from the data through trend analysis was performed.

• Journal of the Korean Data and Information Science Society
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• 제18권2호
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.

• International Journal of Reliability and Applications
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• 제14권2호
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• pp.55-70
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• 2013

This paper deals with the Bayesian analysis of the failure data of a repairable mechanical system subject to minimal repairs and periodic overhauls. The effect of overhauls on the reliability of the system is modeled by a proportional age reduction model and the failure process between two successive overhauls is assumed to be 2-parameter Engelhardt-Bain process (2-EBP). Power Law Process (PLP) model has a disadvantage which 2-EBP can overcome. On the basis of the observed data and of a number of suitable prior densities, point and interval estimation of model parameters, as well as quantities of relevant interest are found. Also hypothesis tests on the effectiveness of performed overhauls have been developed using Bayes factor. Sensitivity analysis of improvement parameter is carried out. Finally, a numerical application is used to illustrate the proposed method.

• International Journal of Reliability and Applications
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• 제8권1호
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• pp.53-66
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• 2007

This paper proposes a new non-homogeneous Poisson process software reliability growth model based on the coverage information. The new model incorporates the coverage information in the fault detection process by assuming that only the faults in the covered constructs are detectable. Since the coverage growth behavior depends on the testing strategy, the fault detection process is first modeled for the general testing strategy and then realized for the uniform testing. Finally the model for the uniform testing is empirically evaluated by applying it to real data sets.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2001년도 춘계학술대회 논문집
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• pp.347-358
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• 2001

In this paper, we apply NHPP model example to s/w process in order to get to know s/w reliability. The test is constructed by a test zig of commercial product loaded real embedded system s/w. It is established to s/w reliability prediction and estimation of real-time embedded system s/w. It is computed the prediction value of cumulative failures, the failure intensity, the reliability and the estimation value of MTTF, Failure Rate. To the more realization of high reliability in the real-time embedded system s/w, if the embedded system s/w is ensured to the test coverage and constructed to stable s/w process ＆ operating system, we can improve the performance and the reliability characteristic of the real-time embedded system s/w.

• 통합자연과학논문집
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• 제10권4호
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• pp.249-257
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• 2017

The main focus when developing software is to improve the reliability and stability of a software system. We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Once software systems are introduced, the software systems used in the field environments are the same as or close to those used in the development-testing environment; however, the systems may be used in many different locations. Development of software system is a difficult and complex process. Generally, existing software reliability models are applied to software testing data and then used to make predictions on the software failures and reliability in the field. In this paper, we present an improved exponential NHPP software reliability model in different development environments, and examine the goodness-of-fit of improved exponential model and other model based on two datasets. The results show that the proposed model fits significantly better than other NHPP software reliability model.

• 품질경영학회지
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• 제39권4호
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• pp.480-485
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• 2011

This paper presents a spare ordering policy for preventive replacement with minimal repair. To analyze the ordering policy, the failure process is modeled by a non-homogeneous Poisson process. Introducing the ordering, repair, downtime, replacement costs and salvage value, we derive the expected cost effectiveness as a criterion of optimality when the lifetime and lead times for the regular and expedited orders are generally distributed random variables. It is shown that, under certain conditions, there exists a finite and unique optimum ordering time which maximizes the expected cost effectiveness. A numerical example is also included to explain the proposed model.