Software Quality Prediction Model with the Aid of Advanced Neural Network with HCS

Software quality is regarded as the highly important factors for assessing the global competitive position of any software product. To assure quality, and to assess the reliability of software products, many software quality prediction models have been proposed in the past decades. In this proposed method we have utilized a hybrid method for quality prediction. The prediction is done with the help of the Advanced Neural network which is incorporated with Hybrid Cuckoo search (HCS) optimization algorithm for better prediction accuracy. The application software is first subjected to test case generation and once the test cases are generated they are applied to advanced neural network for the prediction of quality. The neural network is improved by utilizing HCS which optimizes the weight factor for improving the prediction. The quality metrics like maintainability and reliability are estimated for predicting the software quality and the results are compared with other existing techniques to verify the effectiveness of our proposed method.