Prediction of software reliability using an auto regressive process

Abstract This paper proposes a procedure for predicting software reliability, using an Auto Regressive (AR) model. The parameters of the models are selected using computationally efficient numerical methods like Singular Value Decomposition ( SVD) and QR factorization. For better prediction of time between failures, the AR models have been selected using Akaike Information Criterion (AIC) and Schwarz's Information Criterion ( SIC). A comparative study with the Jelinski-Moranda (JM) and Schick-Wolverton ( SW) models has been performed. Some real life data has been used for illustration purposes.

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