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Software reliability is one of the most commonly discussed research issue in the field of software engineering. In this paper we evaluate the reliability of component based software using Adaptive Neuro-Fuzzy inference system. The proposed model considers the factors particular to component based software that affects its reliability. The hybrid neural network used in ANFIS is trained using the data set obtained from a survey. This neural network in turn guides the rule base of the fuzzy inference system. Our ANFIS model is validated against the data obtained from survey of various existing component based software designs. An evaluation model based on Mamdani fuzzy inference system is also proposed. The performance analysis of ANFIS model is done by comparing its accuracy in determining correct outputs with that of the FIS model. The ANFIS model is optimized to obtain evaluation near to the empirical results. Experimental results show that ANFIS based evaluation model performs better than the corresponding FIS model. [ABSTRACT FROM AUTHOR]