• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.761-769
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• 2002

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. The testing time on the right is truncated in this model. The instantaneous failure rate, mean-value function, error detection rate, reliability of the software, estimation of parameters and the simple applications of this model are discussed .

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.49-54
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• 2012

In this paper, a software policy considering testing time and the number of errors corrected is presented. The software is tested until a specified testing time or the time to a specified number of errors are corrected, whichever comes first. The model includes the cost of error correction and software testing during the testing time, and the cost of error correction during operation. It is assumed that the length of software life cycle has no bounds, and the error correction follows an non-homogeneous Poisson process. An expression for the total cost under the policy is derived. It is shown that the model includes the previous models as special cases.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.1995-2006
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• 1997

Because of formlessness and sightlessness of software, sytematic quality management is hard to implement. But we attemped collective quality management as hardware production by configuration management and settled on software quality management standard outlines. We are implementing efficient quality management by software quality management according as these standard guidelines. In this study, we study error management supporting functions as an attempt of development of software quality management supporting system which can support quality management activity by reduction and early finding of error input, and represent various visual output elements which can help error management supporting functions. And we represent the background of construction of this software quality management system and searched effects which we can get when we use the error management supporting function.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.75-80
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• 2012

There are many problems that cause the process improvement of software and hardware, personality errors during software development. This paper propose the quantitative analysis of error that removes and manages the system problems as well.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.553-560
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• 2003

Can presume number of software failure or remaining fault that is expected with test data that is collected by decided time using SRGM that is studied until present. Therefore, can forecast software reliability achievement degree and software reliability use step. But, reliability evaluation according to if choose any model can change. Therefore, we present SRGM that consider test cost to error detection and error delete cost as SRGM that consider error delete cost in this research. Using this SRGM, can presume number of remaining fault in software, reliability and optimal release time.

• 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 the Korea Society of Computer and Information
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• v.29 no.6
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• pp.89-100
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• 2024

The primary goal of software testing is to identify and correct errors within software. A key challenge in this process is error masking, where errors disappear internally before reaching the output. This paper investigates the causes and characteristics of error masking, which complicates software testing. The study involved injecting artificial errors into three software programs to examine the extent of error masking by various test cases and to explore the underlying reasons. The experiment yielded four major findings. First, about 50% of the error masking occurred because the errors were not executed. Second, among various operators, logical and arithmetic operators masked errors less frequently, while relational and temporal operators tended to mask errors more extensively. Third, certain test cases demonstrated exceptional effectiveness in propagating errors to the output. Fourth, the type of error injected influenced the masking effect.

• 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.

• Journal of The Korean Association of Information Education
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• v.2 no.1
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• pp.35-51
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• 1998

Software reliability growth model is one of the evaluation methods, software quality which quantitatively calculates the software reliability based on the number of errors detected. For correct and precise evaluation of reliability of certain software, the reliability model, which is considered to fit dose to real data should be selected as well. In this paper, the optimal model for specific test data was selected one of among five software reliability growth models based on NHPP(Non Homogeneous Poission Process), and in result reliability estimating scales(total expected number of errors, error detection rate, expected number of errors remaining in the software, reliability etc) could obtained. According to reliability estimating scales obtained, Software development and predicting optimal release point and finally in conducting systematic project management.