Analysis of Resilient Back-Propagation for Improving Software Process Control
In this paper, the authors present the application of the neural network for the identification of Reusable Software modules in Oriented Software System. Metrics are used for the structural analysis of the different procedures. The values of Metrics will become the input dataset for the neural network systems. Training Algorithm based on Neural Network is experimented and the results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). Hence, the proposed model can be used to improve the productivity and quality of software development.