Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
A software reliability growth model for an error-removal phenomenon
Software Engineering Journal
A Model for Software Development Effort and Cost Estimation
IEEE Transactions on Software Engineering
Analysis of error processes in computer software
Proceedings of the international conference on Reliable software
Modelling the Fault Correction Process
ISSRE '01 Proceedings of the 12th International Symposium on Software Reliability Engineering
An integration of fault detection and correction processes in software reliability analysis
Journal of Systems and Software - Special issue: Selected papers from the 4th source code analysis and manipulation (SCAM 2004) workshop
International Journal of Systems Science
| Hi-index | 0.00 |
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.