Neural Network Based Test Case Prioritization in Software Engineering

Abstract

The test case prioritization is the technique of Regression testing in which test cases are prioritized according to the changes which are done in the project. This work is based on manual slicing and automated slicing for test case prioritization to detect maximum number of faults from the project in which some changes are done for the new version release. The slicing is the technique which will divide the whole project function wise and detect associated functions. To increase the fault detection rate the automated technique is being applied in which multi-objective algorithm is been applied which calculates the function importance in the automated manner. In the simulation it is being analyzed that fault detection rate is increased and execution time is reduced with the implementation of automated test case prioritization as compared to manual test case prioritization in regression testing.