Fault Localization Method Generated by Regression Test Cases on the Basis of Genetic Immune Algorithm
Hui Zhang · 2016
The relation between regression testing and software debugging in software development is iteration. However, regression testing cases cannot be applied directly to fault localization in software debugging because of its different purposes. Some researchers proposed fault localization oriented regression testing cases reduction method, but it can do nothing to solve code changes in regression testing. Thus, in order to improve the quality of fault localization oriented regression testing cases, this paper puts forward the fault localization method generated by regression testing cases to improve genetic algorithm (GA) local convergence. GA and artificial immune algorithm (AIA) are combined, together with approaches of affinity calculation, concentration calculation, crossing and variation to enhance the quality of regression testing cases. And the experiment results show that the efficiency of the fault localization of regression testing cases generation in this paper is higher than the initial one and the GA based one.