Software reliability analysis models
IBM Journal of Research and Development
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Probability and Statistics with Reliability, Queuing and Computer Science Applications
Software Reliability Growth Modeling: Models and Applications
IEEE Transactions on Software Engineering
SREPT: Software Reliability Estimation and Prediction Tool
TOOLS '00 Proceedings of the 11th International Conference on Computer Performance Evaluation: Modelling Techniques and Tools
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
IEEE Transactions on Software Engineering
An autoregressive time series software reliability growth model with independent increment
MMACTE'05 Proceedings of the 7th WSEAS International Conference on Mathematical Methods and Computational Techniques In Electrical Engineering
A Bayesian Inference Tool for NHPP-Based Software Reliability Assessment
FGIT '09 Proceedings of the 1st International Conference on Future Generation Information Technology
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The software reliability growth models (such as NHPP models) are frequently used in software reliability prediction. Estimation of parameters in these models is often done by point estimation. However, some numerical problems arise and make the actual computation hard, especially for automated reliability prediction tools. Here confidence interval computation in Goel-Okumoto model and S-shaped model is studied.The upper and the lower bounds of the parameters can be obtained. For reliability prediction, we implement a simplified Bayesian approach, which delivers improved results. The bounds on the predicted reliability are also computed. Furthermore, numerical problems encountered in earlier point estimation methods are removed by this approach. Our results thus can be used as an important part of the assessment of software quality.