• Title/Summary/Keyword: NHPP (Nonhomogeneous Poisson Process)

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The Bayesian Analysis for Software Reliability Models Based on NHPP (비동질적 포아송과정을 사용한 소프트웨어 신뢰 성장모형에 대한 베이지안 신뢰성 분석에 관한 연구)

  • Lee, Sang-Sik;Kim, Hee-Cheul;Kim, Yong-Jae
    • The KIPS Transactions:PartD
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    • v.10D no.5
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    • pp.805-812
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    • 2003
  • This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP; expressions are given for several performance measure. The parametric inferences of the model using Logarithmic Poisson model, Crow model and Rayleigh model is discussed. Bayesian computation and model selection using the sum of squared errors. The numerical results of this models are applied to real software failure data. Tools of parameter inference was used method of Gibbs sampling and Metropolis algorithm. The numerical example by T1 data (Musa) was illustrated.

A Bayesian Inference for Power Law Process with a Single Change Point

  • Kim, Kiwoong;Inkwon Yeo;Sinsup Cho;Kim, Jae-Joo
    • International Journal of Quality Innovation
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    • v.5 no.1
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    • pp.1-9
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    • 2004
  • The nonhomogeneous poisson process (NHPP) is often used to model repairable systems that are subject to a minimal repair strategy, with negligible repair times. In this situation, the system can be characterized by its intensity function. There have been many NHPP models according to intensity functions. However, the intensity function of system in use can be changed because of repair or its aging. We consider the single change point model as the modification of the power law process. The shape parameter of its intensity function is changed before and after the change point. We detect the presence of the change point using Bayesian methodology. Some numerical results are also presented.

The Comparative Study of NHPP Software Reliability Model Exponential and Log Shaped Type Hazard Function from the Perspective of Learning Effects (지수형과 로그형 위험함수 학습효과에 근거한 NHPP 소프트웨어 신뢰성장모형에 관한 비교연구)

  • Kim, Hee Cheul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.2
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    • pp.1-10
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    • 2012
  • In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure nonhomogeneous Poisson process models presented and the life distribution applied exponential and log shaped type hazard function. 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 could be confirmed. This paper, a failure data analysis of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and coefficient of determination.

The Comparative Study for Software Reliability Models Based on NHPP (NHPP에 기초한 소프트웨어 신뢰도 모형에 대한 비교연구)

  • Gan, Gwang-Hyeon;Kim, Hui-Cheol;Lee, Byeong-Su
    • The KIPS Transactions:PartD
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    • v.8D no.4
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    • pp.393-400
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    • 2001
  • This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

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Comparative Study on the Performance of Finite Failure NHPP Software Development Cost Model Based on Inverse-type Life Distribution (Inverse-type 수명분포에 근거한 유한고장 NHPP 소프트웨어 개발비용 모형의 성능에 관한 비교 연구)

  • Seung-Kyu Park
    • The Journal of the Korea institute of electronic communication sciences
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    • v.18 no.5
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    • pp.935-944
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    • 2023
  • In this study, the Inverse-type (: Inverse-Exponential, Inverse-Rayleigh) life distribution, which is known to be suitable for reliability research, was applied to a software development cost model based on finite failure NHPP(: Nonhomogeneous Poisson Process), and then the attributes that determine the model's performance were analyzed. Additionally, to evaluate the efficiency of the model, it was compared with the Goel-Okumoto basic model. The performance of the model was analyzed using failure time data, and MLE (: Maximum Likelihood Estimation) was applied to calculate the parameters. In conclusion, first, as a result of analyzing m(t), which determines the development cost, the Inverse-Exponential model was efficient due to its small error in the true value. Second, as a result of analyzing the release time along with the development cost, the Inverse-Rayleigh model was confirmed to be the best. Third, as a result of comprehensive evaluation of the attributes (m(t), cost, and release time) of the proposed model, the Inverse-Rayleigh model had the best performance. Therefore, if software developers can effectively utilize this research data in the early process, they will be able to proactively explore and analyze attributes that affect cost.

The Comparative Study for Property of Learning Effect based on Truncated time and Delayed S-Shaped NHPP Software Reliability Model (절단고정시간과 지연된 S-형태 NHPP 소프트웨어 신뢰모형에 근거한 학습효과특성 비교연구)

  • Kim, Hee Cheul
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.4
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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.

A Study on Optimal Software Maintenance Policies with Warranty Period (보증기기간을 고려한 최적 소프트웨어의 보전정책 연구)

  • Nam, Kyung-H.;Kim, Do-Hoon
    • Journal of Korean Society for Quality Management
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    • v.39 no.2
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    • pp.170-178
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    • 2011
  • In general, a software fault detection phenonenon is described by a software reliability model based on a nonhomogeneous Poisson process(NHPP). In this paper, we propose a software reliability growth model considering the differences of the software environments in both the testing phase and the operational phase. Also, we consider the problem of determining the optimal release time and the optimal warranty period that minimize the total expected software cost which takes account of periodic software maintenance(e.g. patch, update, etc). Finally, we analyze the sensitivity of the optimal release time and warranty period based on the fault data observed in the actual testing process.

A Study on Software Reliability Assessment Model of Superposition NHPP (중첩 NHPP를 이용한 소프트웨어 신뢰도 평가 모형 연구)

  • Kim, Do-Hoon;Nam, Kyung-H.
    • Journal of Korean Society for Quality Management
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    • v.36 no.1
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    • pp.89-95
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    • 2008
  • In this paper, we propose a software reliability growth model based on the superposition cause in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

Frameworks for NHPP Software Reliability Growth Models

  • Park, J.Y.;Park, J.H.;Fujiwara, T.
    • International Journal of Reliability and Applications
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    • v.7 no.2
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    • pp.155-166
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    • 2006
  • Many software reliability growth models (SRGMs) based on nonhomogeneous Poisson process (NHPP) have been developed and applied in practice. NHPP SRGMs are characterized by their mean value functions. Mean value functions are usually derived from differential equations representing the fault detection/removal process during testing. In this paper such differential equations are regarded as frameworks for generating mean value functions. Currently available frameworks are theoretically discussed with respect to capability of representing the fault detection/removal process. Then two general frameworks are proposed.

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Reliability Analysis Procedures for Repairable Systems and Related Case Studies (수리 가능 시스템의 신뢰성 분석 절차 및 사례 연구)

  • Lee, Sung-Hwan;Yum, Bong-Jin
    • Journal of the Korea Institute of Military Science and Technology
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    • v.9 no.2 s.25
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    • pp.51-59
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    • 2006
  • The purpose of this paper is to present reliability analysis procedures for repairable systems and apply the procedures for assessing the reliabilities of two subsystems of a specific group of military equipment based on field failure data. The mean cumulative function, M(t), the average repair rate, ARR(t), and analytic test methods are used to determine whether a failure process follows a renewal or non-renewal process. For subsystem A, the failure process turns out to follow a homogeneous Poisson process, and subsequently, its mean time between failures, availability, and the necessary number of spares are estimated. For subsystem B, the corresponding M(t) plot shows an increasing trend, indicating that its failure process follows a non-renewal process. Therefore, its M(t) is modeled as a power function of t, and a preventive maintenance policy is proposed based on the annual mean repair cost.