Package Level Test Case Minimization for Bug Prediction using Linear Regression Machine Learning Approach - Taneja, Divya; Singh, Rajvir; Singh, Ajmer (International Journal of Computer Sciences and Engineering, 2019)
With the growing complexities in Object Oriented (OO) software, the number of bugs present in the software module is increased. In this paper, a technique has been presented for minimization of test cases for the OO systems. The Camel 1.6.1 open source software was used the evaluation of proposed technique. The mathematical model used in the proposed methodology was generated using the open source software WEKA by selecting effective Object Oriented (OO) metrics. Ineffective and effective Object Oriented metrics were recognized by using the techniques based on feature selection to generate test cases that cover fault proneness classes of the software. The defined methodology used only effective metrics for assigning weights to test paths for minimization. The results show the significant improvements.