• Convergence Security Journal
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• v.12 no.1
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• pp.9-16
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• 2012

Due to the large scale application of software systems, software reliability plays an important role in software developments. In this paper, a software reliability growth model (SRGM) is proposed for testing time. The testing time on the right is truncated in this model. The intensity function, mean-value function, reliability of the software, estimation of parameters and the special applications of Pareto NHPP model are discussed. This paper, a numerical example 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, depended on difference between predictions and actual values, were efficient using the mean square error and $R_{SQ}$.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.673-682
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• 2005

In this paper, we generalize the software reliability growth model by assuming that the testing cost and maintenance cost are random and adopt the Bayesian approach to determine the optimal software release time. Numerical examples are provided to illustrate the Bayesian method for certain parametric models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.14
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• pp.45-48
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• 1986

This paper studies reliability growth model in redundancy allocation of Parallel-series system in which several series system is linked parallelly, The model is generalized by system redundancy of sub-system that have components redundancy. The stage of components in each sub-system is established differently. At the same time by assigned the different number of constraints to the sub-system, this paper deals with rather practical reliability growth model.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.875-881
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• 2008

This paper first discusses the existing non-homogeneous Poisson process(NHPP) software reliability growth model(SRGM) frameworks with respect to capability of representing software reliability growth phenomenon. As an enhancement of representational capability a new general coverage-based NHPP SRGM framework is developed. Issues associated with application of the new framework are then considered.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.852-861
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• 2000

Software reliability growth models are used in testing stages of software development to model the error content and time intervals betwewn software failures. In this paper, using priors for the number of fault with the negative binomial distribution nd the error rate with gamma distribution, Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability. For model selection, we explored the sum of the relative error, Braun statistic and median variation. In Bayesian computation process, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carolo method to compute the posterior distribution. Using simulated data, Bayesian inference and model selection is studied.

• Journal of Information Technology Applications and Management
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• v.12 no.2
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• pp.1-13
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• 2005

This paper proposes a software-reliability growth model incoporating the amount of testing effort expended during the software testing phase after developing it. The time-dependent behavior of testing effort expenditures is described by a Logistic 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, 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 curve 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.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.278-285
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• 2012

Purpose: Weapon systems have the long life cycle unlike the consumer product. Thus, the reliability of weapon system is improved during the life cycle through the steady technical change. In this paper, we deal with the method of evaluating the reliability of weapon system with the field failure data. Methods: Especially, we present how to gather the field failure data and evaluate the reliability through the case of K-series weapon system. To evaluate reliability, the reliability growth model is used and the result is discussed. Results: It is steadily improved the reliability of K-series weapon system deployed from 2000 to 2004. The frequency of the failures that affect the mission is largely reduced and MTBMF(mean time between mission failure) is also improved. Conclusion: We can guess the trend of the reliability of weapon system with the field data through this study. Furthermore, it can be used to improve the reliability and make maintenance policy.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.29-38
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• 1998

We summarize, in this paper, that we have learned from the slftwar reliability analysis of a large switching software composed of functional blocks which form slotware units. To determine the time of management activity related to sopftware reliability growth, we review the process of detection and correction of software failures. Also we apply the two softwre reliability frowth model, Goel-Okumoto and S-shaped model, to estimate the global software reliability growth to a set of failure found during period of the system test. The analysis methods and results can be applied to other large software development projects.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.615-621
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• 1999

On the aspect of on-time and development resource use, it is very important to predict the software release time during the software development process. In this paper, we present the optimal release problem based on the evaluation indicator and cost evaluation. And also we show the optimal release point considered with both of them. We applied the Exponential Software Reliability Growth Model(E-SRGM) and Testing-effort dependent Software Reliability Growth Model(Te-SRGM) and decided the software release time according to software reliability indicator. As a result of two models comparison, we verify the Te-SRGM is more adopted in our switching system software.