Searching inside group approach for combination test suite reduction

Abstract

For generating the combination test suite, we have proposed a combination test data global optimization mechanism. Firstly, an encoding process is used to create a one-to-one correspondence between each test case in its complete set and the gene in a binary code sequence. Based on this process, the combination test data generating problem has been translated into a binary genetic code optimization problem. Then, the ethnic group evolution algorithm (EGEA) is used to search the binary code space to find the optimal binary code sequence. In order to refine the genetic structure of each group, a novel ethic group searching approach, searching inside group process is presented. The simulations show this searching process is feasible, which improves the efficiency of optimizing genetic structure and reducing test case set observably.