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Computer Engineering ›› 2009, Vol. 35 ›› Issue (6): 213-215. doi: 10.3969/j.issn.1000-3428.2009.06.075

• Artificial Intelligence and Recognition Technology • Previous Articles     Next Articles

Study of Test Suite Minimization Based on Ant Colony Algorithm

DING Ge-jian1, ZHENG Yan-ni2, ZHANG Lu2   

  1. (1. College of Mathematics Science and Information, ZheJiang Normal University, Jinghua 321004;2. College of Computer Science, Sichuan University, Chengdu 610064)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-03-20 Published:2009-03-20

基于蚁群算法的测试用例集最小化研究

丁革建1,郑燕妮2,张 璐2   

  1. (1. 浙江师范大学数理信息学院,金华 321004;2. 四川大学计算机学院,成都 610064)

Abstract: Test suite minimization aims at testing all the test objectives adequately with the least number of test suites. As abstracts each test case as independent node, this paper brings forward a new test suite minimization method based on ant colony algorithm and its detail steps by constructing virtual ant colony and updating heuristic information dynamically. Furthermore, this thesis validates the method by designing algorithm and doing emulate program. The experimental data proves that the method is effective and feasible.

Key words: ant colony algorithm, test suite minimization, pheromone, heuristic information

摘要: 测试用例集最小化的目的是用尽可能少的测试用例充分测试给定的被测目标。把每个待测用例抽象成独立的节点,通过构造虚拟蚁群以及采用启发信息的动态更新,提出一种新的基于蚁群算法的测试用例集最小化方法及具体实现步骤。并编写算法,运行仿真程序对基于蚁群算法的测试用例集最小化方法进行验证,对实验结果的分析证明了该算法的可行性和有效性。

关键词: 蚁群算法, 测试用例集最小化, 信息素, 启发信息

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