Test Case Reduction Based on Program Invariant and Genetic Algorithm

Test case reduction is the focus of the field of software testing. In this paper, we integrate random testing methods, invariant technology and genetic algorithms for test case reduction. Program invariant here refers to the properties at some points of program, it can reveal the extent of program data coverage and other valuable information. We evaluate the parent program invariants to filter corresponding set of test cases, and keep the better ones on the offspring. Generation by generation, we can get the final reduced set of test cases. This method is easy to automate. Experimental results and analysis show that compared to similar methods, at the same coverage conditions, the method proposed in this paper have higher efficiency and can get better set of test cases.