基于支持向量机的测试用例自动生成方法
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摘要
针对软件测试中功能测试用例集的数量较大且覆盖率较低的问题,提出一种基于支持向量机的测试用例自动生成方法。利用PICT测试工具产生输入参数的两组合或三组合的数据集作为典型样本集,为待测试软件的输入输出关系训练SVM网络功能模型。实验结果表明,训练好的模型可有效地预测出n-way组合的输入数据对应的期望结果,实现自动生成数量较小且覆盖率更高的测试用例集。
Aiming at the problems that the number of test cases of functional testing is pretty high and the coverage of it is really low in software testing,a method that based on the support vector machine(SVM)was proposed to generate test cases automatically.The data sets generated from PICT testing tool which produced 2-way or 3-way combinations of input parameters were taken as typical samples and SVM was used to train the functional model that was taken as the input-output relationship substitute for software under test.Experimental results show that the trained model can effectively predict the expected result which is corresponding to n-way combinations of input data,reaching the goal of automatically generating the test cases with smaller quantity and higher coverage.
Aiming at the problems that the number of test cases of functional testing is pretty high and the coverage of it is really low in software testing,a method that based on the support vector machine(SVM)was proposed to generate test cases automatically.The data sets generated from PICT testing tool which produced 2-way or 3-way combinations of input parameters were taken as typical samples and SVM was used to train the functional model that was taken as the input-output relationship substitute for software under test.Experimental results show that the trained model can effectively predict the expected result which is corresponding to n-way combinations of input data,reaching the goal of automatically generating the test cases with smaller quantity and higher coverage.
引文
[1]WANG Jian,LIU Yanheng,LIU Xuelian.Model for cascading faults in complex software[J].Chinese Journal of Computer,2011,34(6):1137-1147(in Chinese).[王健,刘衍珩,刘雪莲.复杂软件的级联故障建模[J].计算机学报,2011,34(6):1137-1147.]
[2]DAI Chenghui.An effective method of test suite reduction[J].Computer Measurement and Control,2014,22(4):1056-1058(in Chinese).[戴成辉.一种有效的约简测试用例的方法[J].计算机测量与控制,2014,22(4):1056-1058.]
[3]ZHANG Weixiang,LIU Wenhong.Test suite generation based on interaction testing and fault tree analysis[J].Computer Science,2014,41(S2):375-378(in Chinese).[张卫祥,刘文红.基于故障树分析与组合测试的测试用例生成方法[J].计算机科学,2014,41(S2):375-378.]
[4]HU Jing,ZHAO Ying.Application of machine learning in optimized generation of software test suite[J].Journal of Shanghai Electric Institute,2010,13(3):162-166(in Chinese).[胡静,赵莹.机器学习在软件测试用例集优化生成中的应用[J].上海电机学院学报,2010,13(3):162-166.]
[5]YOU Feng,ZHAO Ruilian,LYU Shanshan.Output domain based automatic test case generation[J].Journal of Computer Research and Development,2016(3):541-549(in Chinese).[尤枫,赵瑞莲,吕珊珊.基于输出域的测试用例自动生成方法研究[J].计算机研究与发展,2016(3):541-549.]
[6]ZHENG Wei,YANG Wei,SONG Haijing,et al.An effective algorithm for automated test suite generation based on artificial neural network rule extraction[J].Journal of Northwestern Polytechnical University,2012,30(2):296-300(in Chinese).[郑炜,杨威,宋海静,等.一种基于规则提取的自动化测试用例生成方法[J].西北工业大学学报,2012,30(2):296-300.]
[7]Shahamiri SR,Wan WK,Ibrahim S,et al.Artificial neural networks as multi-networks automated test oracle[J].Automated Software Engineering,2012,19(3):303-334.
[8]ZHAO Yongbin,ZHU Jiagang,LU Xiao.Method for application of SVM into test case generation[J].Computer Application Research,2015,32(1):115-120(in Chinese).[赵咏斌,朱嘉钢,陆晓.SVM应用于测试用例生成的方法[J].计算机应用研究,2015,32(1):115-120.]
[9]NIE Changhai,JIANG Jing.Optimization of configurable greedy algorithm for covering arrays generation[J].Journal of Software,2013(7):1469-1483(in Chinese).[聂长海,蒋静.覆盖表生成的可配置贪心算法优化[J].软件学报,2013(7):1469-1483.]
[10]LIAO Jianfeng,CAI Xiantao.Selection strategies on use case suites of pairwise combinatorial testing[J].Computer Engineering and Applications,2012,48(11):65-70(in Chinese).[廖剑锋,蔡贤涛.组合测试中用例集的选择策略[J].计算机工程与应用,2012,48(11):65-70.]
[11]WANG Haiyan,LI Jianhui,YANG Fenglei.Overview of support vector machine analysis and algorithm[J].Application Research of Computers,2014,31(5):1281-1286(in Chinese).[汪海燕,黎建辉,杨风雷.支持向量机理论及算法研究综述[J].计算机应用研究,2014,31(5):1281-1286.]
[12]LI Zhenxiang,WANG Wenjian,GUO Husheng.SVM classification algorithm for solving multi-class imbalance data[J].Computer Engineering and Design,2014(7):2499-2503(in Chinese).[李珍香,王文剑,郭虎升.处理多类不平衡数据的SVM分类算法[J].计算机工程与设计,2014(7):2499-2503.]
[13]WANG Xiaochuan.MATLAB neural network analysis of 43cases[M].Beijing:Beijing University of Aeronautics and Astronautics Press,2013(in Chinese).[王小川.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社,2013.]
[14]WANG Wei,MA Yongqiang,PENG Qiang.Application of SVM multi-classifier on license plate character recognition[J].Computer Engineering and Design,2011,32(9):3166-3169(in Chinese).[王伟,马永强,彭强.SVM多类分类器在车牌字符识别中的应用[J].计算机工程与设计,2011,32(9):3166-3169.]
[2]DAI Chenghui.An effective method of test suite reduction[J].Computer Measurement and Control,2014,22(4):1056-1058(in Chinese).[戴成辉.一种有效的约简测试用例的方法[J].计算机测量与控制,2014,22(4):1056-1058.]
[3]ZHANG Weixiang,LIU Wenhong.Test suite generation based on interaction testing and fault tree analysis[J].Computer Science,2014,41(S2):375-378(in Chinese).[张卫祥,刘文红.基于故障树分析与组合测试的测试用例生成方法[J].计算机科学,2014,41(S2):375-378.]
[4]HU Jing,ZHAO Ying.Application of machine learning in optimized generation of software test suite[J].Journal of Shanghai Electric Institute,2010,13(3):162-166(in Chinese).[胡静,赵莹.机器学习在软件测试用例集优化生成中的应用[J].上海电机学院学报,2010,13(3):162-166.]
[5]YOU Feng,ZHAO Ruilian,LYU Shanshan.Output domain based automatic test case generation[J].Journal of Computer Research and Development,2016(3):541-549(in Chinese).[尤枫,赵瑞莲,吕珊珊.基于输出域的测试用例自动生成方法研究[J].计算机研究与发展,2016(3):541-549.]
[6]ZHENG Wei,YANG Wei,SONG Haijing,et al.An effective algorithm for automated test suite generation based on artificial neural network rule extraction[J].Journal of Northwestern Polytechnical University,2012,30(2):296-300(in Chinese).[郑炜,杨威,宋海静,等.一种基于规则提取的自动化测试用例生成方法[J].西北工业大学学报,2012,30(2):296-300.]
[7]Shahamiri SR,Wan WK,Ibrahim S,et al.Artificial neural networks as multi-networks automated test oracle[J].Automated Software Engineering,2012,19(3):303-334.
[8]ZHAO Yongbin,ZHU Jiagang,LU Xiao.Method for application of SVM into test case generation[J].Computer Application Research,2015,32(1):115-120(in Chinese).[赵咏斌,朱嘉钢,陆晓.SVM应用于测试用例生成的方法[J].计算机应用研究,2015,32(1):115-120.]
[9]NIE Changhai,JIANG Jing.Optimization of configurable greedy algorithm for covering arrays generation[J].Journal of Software,2013(7):1469-1483(in Chinese).[聂长海,蒋静.覆盖表生成的可配置贪心算法优化[J].软件学报,2013(7):1469-1483.]
[10]LIAO Jianfeng,CAI Xiantao.Selection strategies on use case suites of pairwise combinatorial testing[J].Computer Engineering and Applications,2012,48(11):65-70(in Chinese).[廖剑锋,蔡贤涛.组合测试中用例集的选择策略[J].计算机工程与应用,2012,48(11):65-70.]
[11]WANG Haiyan,LI Jianhui,YANG Fenglei.Overview of support vector machine analysis and algorithm[J].Application Research of Computers,2014,31(5):1281-1286(in Chinese).[汪海燕,黎建辉,杨风雷.支持向量机理论及算法研究综述[J].计算机应用研究,2014,31(5):1281-1286.]
[12]LI Zhenxiang,WANG Wenjian,GUO Husheng.SVM classification algorithm for solving multi-class imbalance data[J].Computer Engineering and Design,2014(7):2499-2503(in Chinese).[李珍香,王文剑,郭虎升.处理多类不平衡数据的SVM分类算法[J].计算机工程与设计,2014(7):2499-2503.]
[13]WANG Xiaochuan.MATLAB neural network analysis of 43cases[M].Beijing:Beijing University of Aeronautics and Astronautics Press,2013(in Chinese).[王小川.MATLAB神经网络43个案例分析[M].北京:北京航空航天大学出版社,2013.]
[14]WANG Wei,MA Yongqiang,PENG Qiang.Application of SVM multi-classifier on license plate character recognition[J].Computer Engineering and Design,2011,32(9):3166-3169(in Chinese).[王伟,马永强,彭强.SVM多类分类器在车牌字符识别中的应用[J].计算机工程与设计,2011,32(9):3166-3169.]