V. B. Singh
Abstract
The progress of software testing is influenced by various uncertainty factors like effort expenditure, skill of test personal, testing tool, defect density, irregular state of open source project, and irregular state of software fault-report phenomena on the bug tracking system. Hence, there is an irregular fluctuation in fault detection/removal rate during testing phase. In software, the independence of failures can hardly be assumed and dependency of faults can also be considered as one of the factor for getting irregular fluctuation. In Literature, various software reliability growth models have been developed by considering fault dependency with various debugging time lag functions. But, none of the models have incorporated irregular fluctuation in their fault detection rate. Therefore, in this paper fault dependency based software reliability growth models have been developed by applying an It ∧o type Stochastic Differential Equations in order to incorporate (i) the irregular fluctuation in the fault detection process due to various uncertainty factor during testing phase and (ii) irregular state of software fault-report phenomena on the bug tracking system. The proposed stochastic differential equation based fault dependency models have been validated using (i) open source software fault count data where software fault-report phenomena on the bug tracking system keep an irregular state and (ii) a fault counting data with minor, major and critical faults. The proposed models have been compared with the existing fault dependency models. Various comparison criteria results for goodness of fit have also been presented in the paper.
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Index Terms
- Measuring reliability growth of software by considering fault dependency, debugging time Lag functions and irregular fluctuation
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