基于三目标搜索的测试用例集约简方法

现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大。针对该问题,提出一种三目标搜索算法。对测试用例覆盖度和运行代价的双目标优先级模型进行细化,给出每个目标的定量细化方法,根据此模型计算出各个用例的优先级,运用到改进蚁群算法中作为各节点的初始信息素值进行优化遍历搜索,将错误检测率作为蚂蚁挑选下一个节点的影响因子,并制定信息素更新规则,使其能够尽快找到最优解。实验结果表明,与贪心算法、基本蚁群算法等相比,该算法得到的测试用例最小集规模较小,具有较高的错误检测率。...

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Published in计算机工程 Vol. 42; no. 3; pp. 84 - 88
Main Author 张妍 傅秀芬
Format Journal Article
LanguageChinese
Published 广东工业大学计算机学院,广州,510006 2016
Subjects
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ISSN1000-3428
DOI10.3969/j.issn.1000-3428.2016.03.015

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Abstract 现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大。针对该问题,提出一种三目标搜索算法。对测试用例覆盖度和运行代价的双目标优先级模型进行细化,给出每个目标的定量细化方法,根据此模型计算出各个用例的优先级,运用到改进蚁群算法中作为各节点的初始信息素值进行优化遍历搜索,将错误检测率作为蚂蚁挑选下一个节点的影响因子,并制定信息素更新规则,使其能够尽快找到最优解。实验结果表明,与贪心算法、基本蚁群算法等相比,该算法得到的测试用例最小集规模较小,具有较高的错误检测率。
AbstractList TP309; 现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大.针对该问题,提出一种三目标搜索算法.对测试用例覆盖度和运行代价的双目标优先级模型进行细化,给出每个目标的定量细化方法,根据此模型计算出各个用例的优先级,运用到改进蚁群算法中作为各节点的初始信息素值进行优化遍历搜索,将错误检测率作为蚂蚁挑选下一个节点的影响因子,并制定信息素更新规则,使其能够尽快找到最优解.实验结果表明,与贪心算法、基本蚁群算法等相比,该算法得到的测试用例最小集规模较小,具有较高的错误检测率.
现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大。针对该问题,提出一种三目标搜索算法。对测试用例覆盖度和运行代价的双目标优先级模型进行细化,给出每个目标的定量细化方法,根据此模型计算出各个用例的优先级,运用到改进蚁群算法中作为各节点的初始信息素值进行优化遍历搜索,将错误检测率作为蚂蚁挑选下一个节点的影响因子,并制定信息素更新规则,使其能够尽快找到最优解。实验结果表明,与贪心算法、基本蚁群算法等相比,该算法得到的测试用例最小集规模较小,具有较高的错误检测率。
Author 张妍 傅秀芬
AuthorAffiliation 广东工业大学计算机学院,广州510006
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FU Xiufen
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DocumentTitleAlternate Test Suite Reduction Method Based on Triple Target Search
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Keywords 双目标模型
优先级
错误检测率
improved ant colony algorithm
软件测试
software test
priority
改进蚁群算法
double target model
error detection rate
Language Chinese
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Notes ZHANG Yan;FU Xiufen;School of Computer Science and Technology,Guangdong University of Technology; Guangzhou 510006, China
31-1289/TP
software test; double target model; priority; error detection rate; improved ant colony algorithm
Existing test case reduction methods basically only take the size and the error detection rate of the optimization set into consideration,rarely paying attention to the test efficiency,so that the test of the opitimization set takes long,and the test cost is high. For this problem,this paper proposes a triple target search algorithm. It details the double target priority model based on the coverage and the test cost of the test case,refines each target's quantitative method,then calculates the priority of each test case according to the model,uses the priority as the initial pheromone value in the improved ant colony algorithm for ergodic optimization,at last regards the error detection rate as the impact factor for the ant to pick the next node,and formulates the pheromone update rule
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PublicationTitle 计算机工程
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Snippet 现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大。针对该问题,提出一种三目标搜索算法。对测...
TP309; 现有测试用例集约简方法基本只考量优化集的规模和错误覆盖率,很少考虑其测试效率,导致优化集的测试运行时间较长,且运行代价较大.针对该问题,提出一种三目标搜索算...
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StartPage 84
SubjectTerms 优先级
双目标模型
改进蚁群算法
软件测试
错误检测率
Title 基于三目标搜索的测试用例集约简方法
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