• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.741-750
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• 2011

In this paper, we derive an software mixed debugging model based on a Markov process, assuming that the length of time to perform the debugging is random and its distribution may depend on the fault type causing the failure. We assume that the debugging process starts as soon as a software failure occurs, and either a perfect debugging or an imperfect debugging is performed upon each fault type. One type is caused by a fault that is easily corrected and in this case, the perfect debugging process is performed. An Imperfect debugging process is performed to fix the failure caused by a fault that is difficult to correct. Distribution of the first passage time and working probability of the software system are obtained; in addition, an availability function of a software system which is the probability that the software is in working at a given time, is derived. Numerical examples are provided for illustrative purposes.

• Journal of Korean Society for Quality Management
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• v.34 no.4
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• pp.133-138
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• 2006

In this paper, we propose a software reliability growth model (SRGM) based on the testing domain, which is isolated by the executed test cases. This model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process. We consider that the fault detection rate of NHPP model is changed in the proposed SRGM. We obtain the maximum likelihood estimate, and compare goodness-of-fit with another existing software reliability growth model.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.73-78
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• 2006

In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• 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 Korean Society for Quality Management
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• v.26 no.1
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• pp.99-107
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• 1998

This paper presents a software reliability model that is based on a nonhomogeneous poisson process. The major contribution of this model is combining multiple failure types with imperfect debugging by use of S-shaped mean value function. The software reliability model allows for three different types of errors: Critical errors are the most difficult to detect and the most expensive to remove. Major errors are moderately difficult to detect and fairly expensive to remove. Minor errors are easy to detect and inexpensive to remove. The model also allows for the introduction of any of these types of errors during the removal of an error. A numerical example is provided to illustrate the above techniques.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.573-584
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• 2010

This paper considers the differences in the software execution environments in the testing phase and the operational phase to determine the optimal release time and warranty period of software systems. We formulate equations for the total expected software cost until the end of the software life cycle based on the NHPP. In addition, we derive the optimal release time that minimizes the total expected software cost for an imperfect debugging software reliability model. Finally, we analyze the sensitivity of the optimal testing and maintenance design related to variation of the cost model parameters based on the fault data observed in the actual testing process, and discuss the quantitative properties of the proposed model.

• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.89-95
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• 2008

In this paper, we propose a software reliability growth model based on the superposition cause in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• Journal of applied mathematics & informatics
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• v.30 no.3_4
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• pp.489-498
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• 2012

Most of the software reliability models are based on black box approach and these models consider the entire software system as a single unit. Present day software development process has changed a lot. In present scenario these models may not give better results. To overcome this problem an improved additive model has been proposed in this paper, to estimate the reliability of software with modular structure. Also the concept of imperfect debugging has been also considered. A maximum likelihood estimation technique has been used for estimating the model parameters. Comparison has been made with an existing model. ${\chi}^2$ goodness of fit has been used for model fitting. The proposed model has been validated using real data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.623-629
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• 2009

In this research, the process of developing software products to users in transfer by considering the warranty period to determine the timing of the release period is a comparative study of models. For the results of demonstration, exponential software reliability model increases the warranty period, the higher the initial period, but shows almost a similar release. In contrast, the optimal release time of imperfect debugging software reliability model, lower the initial warranty period, but the pattern is expected to rise slightly larger. The proposed model, extreme value distribution model, pattern of the optimal release time gradually increase, have a form that can be drawn. These research results through, warranty period and release the software developers understand the relationship between the optimal time for software development by using advance information could do is feed.