• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.57-64
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• 2000

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model, Numerical examples are provided for illustrative purposes.

• 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.

• The Korean Journal of Applied Statistics
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• v.21 no.6
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• pp.997-1006
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• 2008

This paper proposes a new model by combining an infinite-server queueing model for multi-task processing software system with a perfect debugging model based on Markov process with two types of faults suggested by Lee et al. (2001). We apply this model for module and integration testing in the testing process. Also, we compute several measure, such as the expected number of tasks whose processes can be completed and the task completion probability are investigated under the proposed model.

• 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.