Empirical Analysis of Fault Predication Techniques for Improving Software Process Control

نویسنده

  • Kamaljit Kaur
چکیده

In this paper, we 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 and Fuzzy Systems. Training Algorithm based on Neural Network and fuzzy clustering are experimented and the results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The results show that Fuzzy Clustering based technique have shown better results than Resilient Backpropagation on the basis of testing data in terms of prediction technique.Hence the proposed model can be used to improve the productivity and quality of software development.

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تاریخ انتشار 2012