Exponential order statistic models of software reliability growth
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Wavelet-based approach for estimating software reliability
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
Advances in Software Engineering - Special issue on Software Quality Assurance Methodologies and Techniques
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In the literature on statistical inference in software reliability, the assumptions of parametric models and random sampling of bugs have been pervasive. We argue that both assumptions are problematic, the first because of robustness concerns and the second due to logical and practical difficulties. These considerations motivate the approach taken in this paper. We propose a nonparametric software reliability model based on the order-statistic paradigm. The objective of the work is to estimate, from data on discovery times observed within a type I censoring framework, both the underlying distribution F from which discovery times are generated and N, the unknown number of bugs in the software. The estimates are used to predict the next time to failure. The approach makes use of Bayesian nonparametric inference methods, in particular, the beta-Stacy process. The proposed methodology is illustrated on both real and simulated data.