Automatic Structural Test Data Generation Using Immune Genetic Algorithm

摘要：

Automatic structural test data generation is a key problem in software testing,which is the most important quality assurance measure currently.Its implementation can not only significantly improve the eriectiveness and efficiency but also reduce the high cost of software testing.As a robust metaheuritStic search method in complex spaces。genetic algorithm(GA)has been applied to test data generation since 1992.Although GA-based test data generation outperforms other approaches,there are still several shortcomings SUCh as slow convergence,time-consuming fitness calculation,population degeneration,and so on.In order to make better performances,this paper proposes a framework for automatic structural test data generation using immune genetic algorithm that can help to decrease probability of population degeneration and to accelerate convergence to the global optimum.

关键词： software testing genetic algorithm test data generation

作者: Chen Yong Zhong Yong Bao Sheng-Li He Fa-Mei

会议类型: 国际会议

会议名称: The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)

会议地点: 成都

会议语种:英文

页码: 688-690

在线出版日期: 2007-12-19（万方平台首次上网日期，不代表论文的发表时间）