A Hybrid Directed Test Suite Augmentation Technique

Abstract

Test suite augmentation techniques are used in regression testing to identify code elements affected by changes and to generate test cases to cover those elements. In previous work, we studied two approaches to augmentation, one using a concolic test case generation algorithm and one using a genetic test case generation algorithm. We found that these two approaches behaved quite differently in terms of their costs and their abilities to generate effective test cases for evolving programs. In this paper, we present a hybrid test suite augmentation technique that combines these two test case generation algorithms. We report the results of an empirical study that shows that this hybrid technique can be effective, but with varying degrees of costs, and we analyze our results further to provide suggestions for reducing costs.