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基于序优化蚁群算法的成对交互测试用例集生成 被引量：2

BUILDING PAIRWISE INTERACTION TEST SUITES WITH OO-ACO
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摘要 为了弥补蚁群算法在评价测试用例集质量方面的缺陷,应用基于序优化蚁群算法生成优先成对交互测试用例集。在生成测试用例时,采用one-test-at-a-time策略,通过序优化蚁群算法生成涵盖更多总增益的测试用例集,对信息素更新采用分阶段方式。仿真实验表明该算法在解的质量和收敛速度方面优于基本蚁群算法。 To compensate for the defects of ant colony algorithm in evaluating the quality of the test suite, a prioritised pairwise interaction test suite is generated with order optimisation--ant colony optimisation （O0-ACO） algorithm. While building the test suites, a one-test-at-a- time policy is adopted; OO-ACO is used to generate the test suite covering more total incremental benefits, and the phased approach is em- ployed to update the pheromone. Simulation experiments show that this algorithm is superior to the basic ant colony algorithm in both the qual- ity of solutions and the speed of convergence.
作者 张驰 王曙燕 孙家泽
机构地区 西安邮电学院计算机学院
出处 《计算机应用与软件》 CSCD 北大核心 2013年第1期71-74,共4页 Computer Applications and Software
基金 国家自然科学基金项目(61050003)
关键词 交互测试 蚁群优化算法 序优化 总增益 Interaction testing Ant colony optimisation Order optimisation Total incremental benefits
分类号 TP301 [自动化与计算机技术—计算机系统结构]
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参考文献12

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共引文献71

同被引文献25

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计算机应用与软件
2013年 第1期

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