Rolling Prediction Based Software Reliability Model Consideration with Learning Curve

Software reliability is an important factor for evaluating software quality in the domain of safety-critical software. The neural network prediction method has been widely used in reliability prediction area. However, Data noise and other issues make this approach easy to falling into local optimum, and reduce the accuracy of the prediction, it also affect the applicability of the model. In this paper, we consider the learning curve effect, and proposed a neural network based reliability prediction, utilize the rolling forecast method to elevate the accuracy and applicability of neural network. The method is validated through three groups of public data sets. And the results show a fairly accurate prediction capability.