A Theoretical Study: The Impact of Cloning Failed Test Cases on the Effectiveness of Fault Localization

Abstract

Statistical fault localization techniques analyze the dynamic program information provided by executing a large number of test cases to predict fault positions in faulty programs. Related studies show that the extent of imbalance between the number of passed test cases and that of failed test cases may reduce the effectiveness of such techniques, while failed test cases can frequently be less than passed test cases in practice. In this study, we propose a strategy to generate balanced test suite by cloning the failed test cases for suitable number of times to catch up with the number of passed test cases. We further give an analysis to show that by carrying out the cloning the effectiveness of two representative fault localization techniques can be improved under certain conditions and impaired at no time.