• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.589-599
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• 2004

Most models assume the complete debugging environments by requiring a complete software correction in quantitative evaluation of software reliability. But, in many case, new faults are involved in debugging works, for complete software correction is impossible. In this paper, software growth model is proposed about incomplete debugging environments by considering the possibility of new faults involvements, and software faults occurrence status are also mentioned about NHPP by considering software faults under software operation environments and native faults owing to the randomly involved faults in operation before test. While, effective quantitative measurements are derived in software reliability evaluation, applied results are suggested by using actual data, and fitnesswith existing models are also compared and analyzed.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.487-493
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• 2007

In this paper, we deal with an optimal software-release problem of determining the time to stop testing and release the software system to the user. The optimal release time problem is considered from maintenance like the periodic distribution of service packs and the unpredictable distribution of patches after the release. Moreover, the environment of software error-detection during operation differs from the environment during testing. This paper proposes the software reliability growth model which incorporates periodic service packs, unpredictable patches and operational environment. Based on the proposed model, we derive optimal release time to minimize total cost composed of fixing an error, testing and maintenance. Using numerical examples, optimal release time is determined and illustrated.

• International Journal of Reliability and Applications
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• v.8 no.1
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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.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.1-12
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• 2006

Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimator and maximum likelihood estimator for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.87-96
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• 2020

In this paper we proposed the test design method of reliability growth management. First, we presented the process for establishing the reliability growth management test design considering the number of failures and the termination test time. Reliability growth analysis of continuous system was performed in accordance with the test design process presented. In case the reliability test result is not met with the reliability target value after more than three failures occurred, the required test times were analyzed that 1,725 hrs for one corrective action, 1,950 hrs for two corrective actions. If the number of failures is less than three, design a reliability demonstration test according to confidence level 80% and 90% was performed using RGA 11 Software. As a result, it is possible to establish the reliability growth management test design with sufficient use of available resources. The results of this study can be used when establishing a test design for assessment of reliability growth management of all continuous systems.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.597-601
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• 2005

Korea Railroad Research Institute(KRRI) developed the Driverless Rubber Tired Korea-AGT(Model: K-AGT) from 1999 to 2004. We have finished the safety and performance tests of K-AGT. Data obtained from this testing can be used to evaluate the growth of reliability. The most widely used traditional growth tracking model is included as IEC International standard. With the tracking model all corrective actions are incorporated during test, called test-fix-test. In the test-fix-test strategy problem modes are found during testing and corrective actions for these problems are incorporated during testing. In this paper, we demonstrated reliability analysis using growth model of driverless rubber tired K-AGT system to prove reliability of development system. Therefore, we introduce the well-known NHPP model and analyze a reliability growth using ReliaSoft's RGA software.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.1-6
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• 1990

This paper deals with software Release policy having a Fixed Operational period after a Software System is released. The underlying Software Reliability Growth is described by J-M Model Optimal of Software Release Time minimizing Total Expected Cost is Obtained.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.659-666
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• 2002

Park, Seo and Kim (12) developed the input domain-based SRGM, which was able to quantitatively assess the reliability of a software system during the testing and operational phases. They assumed perfect debugging during testing and debugging phase. To make this input domain-based SRGM more realistic, this assumption should be relaxed. In this paper we generalize the input domain-based SRGM under imperfect debugging. Then its statistical characteristics are investigated.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.147-160
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• 2001

The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.