An Efficient Technique for Software Fault Prediction in Variance Analysis
In this paper, the authors are using machine learning method for predicting fault, i.e. support vector machine to predict the accuracy of the model predicted. The proposed models are validated using dataset collected from open source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results give the users' an idea about that the design predict by the support vector machine outperformed the entire the current models.