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计算机系统应用英文版:2018,27(3):105-111
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基于DBSCAN算法的测试用例优化方法
(1.浙江理工大学 信息学院, 杭州 310018;2.桂林电子科技大学 广西可信软件重点实验室, 桂林 541004)
Test Case Optimization Method Based on DBSCAN Algorithm
(1.School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 31008, China;2.Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China)
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Received:May 25, 2017    Revised:June 16, 2017
中文摘要: 在软件测试研究领域,测试用例约简一直以来都是研究的重点,目前的一些研究利用测试需求之间复杂的相互关系得到约简的测试需求集,在此基础上可以优化对应的测试用例集,但单个测试需求所对应的测试用例集可能是一个密度分布且数量较大的集合.对单个测试需求所对应的测试用例集合进行合理优化约简,本文在这个方面做了深入的研究和探索,提出了两种基于黑盒测试的类等价划分和类边界值分析策略.基于DBSCAN算法提出了科学合理的参数取值方法,提高了算法的适应问题程度和效率,结合优化的算法和两种策略从而得到优化约简的测试用例集.
中文关键词: 黑盒测试  约简  DBSCAN算法  参数取值
Abstract:In software testing field, test case reduction has been a research hotspot for a long time. Some researches currently use the complex relationship between test requirements for the test suites of test case, which can optimize the corresponding test suites on this basis. But the corresponding test case of a single test requirement may be a collection of density distribution in large quantities. This paper does an in-depth research and exploration on how to rationally optimize test case for the corresponding test suits of a single test requirement in the premise of test case. It proposes two classes based on black box testing equivalence partitioning and boundary value analysis strategy. Based on DBSCAN algorithm, it proposes a scientific and reasonable parameter selection method, and improves the adaptation degree and efficiency of algorithm. Combined with optimization algorithm and two strategies, it gets the optimal reduction set of test cases.
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基金项目:国家自然科学基金(61502430,61379036,61562015);广西自然科学重点基金(2015GXNSFDA139038);浙江理工大学521人才培养计划项目
引用文本:
包晓安,鲍超,滕赛娜,张唯,张娜,钱俊彦.基于DBSCAN算法的测试用例优化方法.计算机系统应用,2018,27(3):105-111
BAO Xiao-An,BAO Chao,TENG Sai-Na,ZHANG Wei,ZHANG Na,QIAN Jun-Yan.Test Case Optimization Method Based on DBSCAN Algorithm.COMPUTER SYSTEMS APPLICATIONS,2018,27(3):105-111