Abstract

The software reliability model is developed considering the number of software failures and the interval time between failures, and is a very useful model for predicting software failures that may occur in the future. In most existing software reliability model, the mean value function is considered to follow a non-homogeneous Poisson process (NHPP). NHPP software reliability model has a mean value function that considers the failure intensity, detection rate, number of remaining failures, and various environments. The Burr distribution can fit a wide range of empirical data. In addition, it was proposed several types of the cumulative functions and has stressed the advantages obtained by the direct use of the cumulative function. The Burr type XII distribution is a continuous probability distribution for a non-negative random variable. In this paper, we propose a new software reliability model with a fault detection rate function of the Burr type XII distribution based on NHPP. We show that the NHPP software reliability model proposed through various criteria shows much better the goodness-of-fit than other existing NHPP software reliability models.

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