Reliability analysis in component-based development via probabilistic model checking
Proceedings of the 15th ACM SIGSOFT symposium on Component Based Software Engineering
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Importance measures provide a sense of the relative priorities of components and can be used to guide the allocation of resources for cost-effective improvement of system reliability starting from the early phases. Uncertainties in model parameters, prevalent in the early phases, can introduce errors into these measures, and hence, importance assessment must account for these parametric uncertainties. In this paper, a framework for importance assessment of a software system within the context of its architecture is proposed. The framework includes two methods; the first one systematically quantifies the confidence intervals in the model parameters, and the second one offers an analytical approach for importance analysis. The two methods in conjunction address the issue of importance assessment in the face of parametric uncertainties. Illustration of the framework using a banking application demonstrates the value and benefits of the methodology. Copyright © 2009 John Wiley & Sons, Ltd. This paper proposes a framework for importance assessment of a software system within the context of its architecture. The framework includes two methods; the first one systematically quantifies the confidence intervals in the model parameters, and the second one offers an analytical approach for importance analysis. A banking application case study illustrates the framework and demonstrates the valuable benefits of the methodology. Copyright © 2009 John Wiley & Sons, Ltd.