Comparision of Artificial Neural Network and Convolutional Neural Network for prediction of Web Application defects

Abstract

Prediction of web application defects analysis is a main difficulty in the software engineering. The prediction of defects analysis helps in giving the best development and safeguarding processes, which concerns with the complete software success. The result of predicting the defects improve the software system quality, dependability, efficiency and reduce the software cost. However, developing well-built bug prediction model could be a complicated task and plenty of techniques are projected within the literature. Prediction of web application defects is a process used to predict the percentage of deformities in the application. This analysis helps to deploy the product which is more efficient and accurate to the society to satisfy the customer needs with minimum cost. Here the percentage accuracy from the defects  considered from various promising datasets is calculated. Based on  that we can analyze the defects that occur in a web application. To achieve this Artificial Neural Networks (ANN), Convolutional Neural Networks(CNN) are considered and also a contrast between the ANN and the CNN methods is drawn and provide the best algorithm to use while predicting the defects in any web application.