• 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.

• 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.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.891-898
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• 2010

In real software development fields, software is unified by several modules that are developed before the software testing period. For the evaluation of software task processing performance, this paper considers the software imperfect debugging model that is proposed by Lee and Park (2003) and presents the measures of a unified software, such as the completion probability of a task which is completed in a time interval and the expected number of the completed tasks. In addition, we suggest a software release policy that satisfies the required level of the expected perfect debugging, completion probability, and availability.