• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4A
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• pp.399-414
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• 2004

In this paper, an evolution of software reliability engineering in a large-scale software project is summarized. The considered software consists of many components, called functional blocks in software of switching system. These functional blocks are served as the unit of coding and test, and the software is continuously updated by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components in software reliability and reliability evolution. We analyze the static characteristics of the software related to software reliability using collected failure data during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of system software, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto(G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources fur a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.29-36
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• 2014

Finite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, proposes the Gompertz distribution reliability model, which made out efficiency application for software reliability. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on mean square error (MSE) and coefficient of determination$(R^2)$, for the sake of efficient model, was employed. Analysis of failure using real data set for the sake of proposing fixed shape parameter of the Gompertz distribution was employed. This analysis of failure data compared with the Gompertz distribution model of shape parameter. In order to insurance for the reliability of data, Laplace trend test was employed. In this study, the proposed Gompertz model is more efficient in terms of reliability in this area. Thus, Gompertz model can also be used as an alternative model. From this paper, software developers have to consider the growth model by prior knowledge of the software to identify failure modes which can was helped.

• 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.

• The Journal of Information Technology
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• v.10 no.2
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• pp.47-64
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-coverage model was reviewed, proposes the exponentiated exponential coverage reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001). In this analysis of software failure data, algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics for the sake of efficient model, was employed.

• Electronics and Telecommunications Trends
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• v.14 no.4 s.58
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• pp.1-9
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• 1999

In this paper, we summarize the lessons learned from the applications of the software reliability engineering to a large-scale software project. The considered software is the software system of the TDX-10 ISDN switching system. The considered software consists of many components, called functional blocks. These functional blocks serve as the unit of coding and test. The software is continuing to be developed by adding new functional blocks. We are mainly concerned with the analysis of the effects of these software components to software reliability and with the analysis of the reliability evolution. We analyze the static characteristics of the software related to software reliability using failure data collected during system test. We also discussed a pattern which represents a local and global growth of the software reliability as version evolves. To find the pattern of software of the TDX-10 ISDN system, we apply the S-shaped model to a collection of failure data sets of each evolutionary version and the Goel-Okumoto (G-O) model to a grouped overall failure data set. We expect this pattern analysis will be helpful to plan and manage necessary human/resources for a new similar software project which is developed under the same developing circumstances by estimating the total software failures with respect to its size and time.

• The Korean Journal of Applied Statistics
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• v.21 no.5
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• pp.813-823
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• 2008

The non-homogeneous Poisson process(NHPP) based software reliability growth models are proved quite successful in practical software reliability engineering. The fault detection rate is usually assumed to be the continuous and monotonic function. However, the fault detection rate can be affected by many factors such as the testing strategy, running environment and resource allocation. This paper describes a parameter estimation of software reliability growth model with change-point problem. We obtain the maximum likelihood estimate(MLE) and least square estimate(LSE), and compare goodness-of-fit.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.119-122
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• 1995

Application of the PWFRM and SRGM for software reliability Prediction offers not only the judging base of model but also themselves with good applicabilty as easy-to-use tool.

• 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.

• Journal of Applied Reliability
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• v.14 no.4
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• pp.225-229
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• 2014

A one-shot device is defined as a product, system, weapon, or equipment that can be used only once. After use, the device is destroyed or must undergo extensive rebuild. Determining the reliability of a one-shot device poses a unique challenge to the manufacturers and users due to the destructive nature and costs of the testing. This paper presents a reliability growth prediction for a one-shot system. It is assumed that 1) test duration is discrete(i.e. trials or rounds); 2) trials are statistically independent; 3) the number of failures for a given system configuration is distributed according to a binomial distribution; and 4) the cumulative expected number of failures through any sequence of configurations is given by AMSAA model. When the system development is represented by three configurations and the number of trials and failures during configurations are given, the AMSAA model parameters and reliability at configuration 3 are estimated by using a reliability growth analysis software. Further, if the reliability growth predictions do not meet the target reliability, the sample size of an additional test is determined for achieving the target reliability.