Isomorphic regression testing: executing uncovered branches without test augmentation

Jie Zhang, Yiling Lou, Lingming Zhang, Dan Hao, Lu Zhang, Hong Mei

Abstract: In software testing, it is very hard to achieve high coverage with the program under test, leaving many behaviors unexplored. To alleviate this problem, various automated test generation and augmentation approaches have been proposed, among which symbolic execution and search-based techniques are the most competitive, while each has key challenges to be solved. Different from prior work, we present a new methodology for regression testing --Isomorphic Regression Testing,which explores the behaviors of the program under test by creating its variants (i.e., modified programs) instead of generating tests. In this paper, we make the first implementation of isomorphic regression testing through an approach named ISON, which creates program variants by negating branch conditions. The results show that ISON is able to additionally execute 5.3% to 80.0% branches that are originally uncovered. Furthermore, ISON also detects a number of faults not detected by a popular automated test generation tool (i.e., EvoSuite) under the scenario of regression testing.