Test Case Prioritization Based on Artificial Immune Algorithm

摘要

Regression testing is an essential and critical part of smart terminal program development. The test case suite is usually preprocessed by test case prioritization technology to improve the efficiency of regression testing. To address the problems of traditional genetic algorithm in solving the test case prioritization problem, this paper proposed a test case prioritization algorithm for intelligent terminal based on artificial immune algorithm. Firstly, different sequences of test case sets were used as the encoding of antibodies to initialize the antibody population; secondly, the Hemming distance was introduced as the concentration index of antibodies to calculate the incentive degree; finally, the antibodies were immunized to find the optimal test case set sequence. The experimental results showed that the algorithm based on the artificial immune algorithm was more capable of global search and less likely to fall into local optimum than the genetic algorithm, which indicated that the artificial immune algorithm was more stable and could better solve the test case prioritization problem.