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Many architecture-based software reliability models were proposed in the past. Regardless of the accuracy of these models, if a considerable uncertainty exists in the estimates of the operational profile and components reliabilities then a significant uncertainty exists in calculated software reliability. Therefore, the traditional way of estimating software reliability by plugging point estimates of unknown parameters into the model may not be appropriate since it discards any variance due to uncertainty of the parameters. In this paper we propose a methodology for uncertainty analysis of architecture-based software reliability models suitable for large complex component based applications and applicable throughout the software life cycle. First, we describe different approaches to build the architecture based software reliability model and to estimate parameters. Then, we perform uncertainty analysis using the method of moments and Monte Carlo simulation which enable us to study how the uncertainty of parameters propagates in the reliability estimate. Both methods are illustrated on two case studies and compared using several criteria.