• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.203-203
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• 1992

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1103-1111
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• 2000

The hyper-geometric distribution software reliability growth model (HGDM) usually assumes that all the software faults detected are perfectly removed without introducing new faults. However, since new faults can be introduced during the test-and-debug phase, the perfect debugging assumption should be relaxed. In this context, Hou, Kuo and Chang [7] developed a modified HGDM for imperfect debugging environment, assuming tat the learning factor is constant. In this paper we extend the existing imperfect debugging HGDM for tow respects: introduction of random sensitivity factor and allowance of variable learning factor. Then the statistical characteristics of he suggested model are studied and its applications to two real data sets are demonstrated.

• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.221-238
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• 2015

Purpose: In this study, A reliability assurance model (or reliability program) is proposed to evaluate the reliability of an armed vehicle. The reliability assurance is performed through the reliability-centered activities during its life cycle of development/design, production, deployment, maintenance, and disposal. Methods: By reflecting the current situations of korea defense industry, a reliability assurance model is built up based on the benchmarking results of world leading companies' best practices in same fields. Results: The proposed reliability program of armed vehicles, which is based on the reliability program of ANSI/GEIA-STD 0009, uses DMAIC process of the six sigma methodology from design phase to testing and evaluation phase. Conclusion: This research is supposed to develop reliability program of armed vehicles by integrating DFSS, DFR and reliability growth process.

• Communications of the Korean Mathematical Society
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• v.31 no.4
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• pp.869-878
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• 2016

This paper presents an ecient fractional shifted Legendre polynomial method to solve the fractional Volterra's model for population growth model. The fractional derivatives are described based on the Caputo sense by using Riemann-Liouville fractional integral operator. The theoretical analysis, such as convergence analysis and error bound for the proposed technique has been demonstrated. In applications, the reliability of the technique is demonstrated by the error function based on the accuracy of the approximate solution. The numerical applications have provided the eciency of the method with dierent coecients of the population growth model. Finally, the obtained results reveal that the proposed technique is very convenient and quite accurate to such considered problems.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.37-45
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• 1992

Common assumption we frequently encounter in early models of software reliability is that no new faults are introduced during the fault removal process. In real life, however, there are situations in which new faults are introducted as a result of imperfect debugging. This study alleviating this assumption by introducting the probability of perfect error-correction is an extension of Littlewood's work. In this model, the system reliability, failure rates, mean time to failure and average failure frequency are obtained. Here, when the probability of perfect error-correction is one, the results appear identical with those of the previous studies. In the respect that the results of previous studies are special cases of this model, the model developed can be considered as a generalized one.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.15-20
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• 2022

This research studied the evaluation of reliability among the software quality characteristics: suitability, reliability, usability, portability, maintainability, performance efficiency, security, and compatibility. It proposes a quantitative evaluation of reliability in the measurement of software quality. This study introduces a method for measuring the failure rate included in maturity during reliability evaluation, which is one of the characteristics of software quality, and is a study with experimental data on how the failure rate changes depending on the form of failure data. Focusing on software testing, the failure rate was measured and compared according to the type of failure data by applying it to the software reliability growth model, focusing on the number of failures per day. The failure rate was measured around the failure time found through the 6-day test, and the failure rate was compared with the failure rate proposed by the international standard ISO/IEC 25023 using the measurement results, and the application was reviewed according to the data type.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. 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. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.231-241
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• 1996

The reliability in software has expand in quality and quantity, also its importance and role are increased. But, a study of software reliability is lack of development. this paper software reliability growth models(SRGM) described by NonHome-geneous Poisson(NHPP)processes. Using actual software error data observed by software testing the SRGM's are composition of error-class, and error-class by three class. this paper made the reliability-model of software using three error- class. The purpose of this study to increase software productivity and to improve software quality. So to achive these goals we focused a study of software reliability model using the error-class.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.443-444
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• 2008

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.409-420
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• 2001

Recently a new approach to evaluation of software reliability, one of important attributes of a software system, during testing has been devised. This approach utilizes test coverage information. The coverage-based software reliability growth models recently appeared in the literature are first reviewed and classified into two classes. Inherent problems of each of the two classes are then discussed and their validity is empirically investigated. In addition, a new mean value function in coverage and a heuristic procedure for selecting the best coverage are proposed.