Novel Approach for Test Case Prioritization Using ACO Algorithm

Abstract

Regression testing is used to retest the component of a system that verifies that after modifications defects are removed from the in effected software. Automation tools are required for these types of testing. 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 test the performance of proposed and existing algorithm MATLAB is being used by considering the dataset of ten projects. Each project has seven functions and four numbers of changes are defined for the regression testing. 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.