首页> 外文会议>International conference on swarm intelligence >Study of an Improved Genetic Algorithm for Multiple Paths Automatic Software Test Case Generation
【24h】

Study of an Improved Genetic Algorithm for Multiple Paths Automatic Software Test Case Generation

机译:用于多路径自动软件测试用例生成的改进遗传算法研究

获取原文

摘要

Automatic generation of test case is an important means to improve the efficiency of software testing. As the theoretical and experimental base of the existing heuristic search algorithm, genetic algorithm shows great superiority in test case generation. However, since most of the present fitness functions are designed by a single target path, the efficiency of the generating test case is relatively low. In order to cope with this problem, this paper proposes an efficiency genetic algorithm by using a novel fitness function. By generating multiple test cases to cover multiple target paths, this algorithm needs less iterations hence exhibits higher efficiency comparing to the existing algorithms. The simulation results have also shown that the proposed algorithm is high path coverage and high efficiency.
机译:自动生成测试用例是提高软件测试效率的重要手段。作为现有启发式搜索算法的理论和实验基础,遗传算法在测试用例生成方面显示出极大的优势。但是,由于大多数当前适应性功能是由单个目标路径设计的,因此生成测试用例的效率相对较低。为了解决这个问题,本文提出了一种利用新的适应度函数的效率遗传算法。通过生成多个测试用例以覆盖多个目标路径,该算法所需的迭代次数更少,因此与现有算法相比具有更高的效率。仿真结果还表明,该算法具有较高的路径覆盖率和较高的效率。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号