Test Data Generation Based on Automatic Division of Path

LIAO Wei-zhi

ACTA ELECTRONICA SINICA ›› 2016, Vol. 44 ›› Issue (9) : 2254-2261.

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ACTA ELECTRONICA SINICA ›› 2016, Vol. 44 ›› Issue (9) : 2254-2261. DOI: 10.3969/j.issn.0372-2112.2016.09.034

Test Data Generation Based on Automatic Division of Path

  • LIAO Wei-zhi1,2
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Abstract

In order to improve the efficiency of test data generation for path coverage,a method for generating test data was proposed,which was based on automatic division of path and artificial fish-swarm (AFS) algorithm.Firstly,the relations between variables and nodes,and between variables and paths,were analyzed.Based on the analysis an algorithm for automatic division of path was presented,which can automatically judge the impact of variables on sub-paths.Secondly,an improved AFS algorithm was developed based on Levy flying and conjugate gradient.By making use of the result of path division and the improved AFS algorithm,a new method for searching test data was proposed.If there exist sub paths that the fish pass through in the process of using AFS to generate test data,the corresponding component of these fish were fixed,so that search space were reduced.Finally,the proposed method was applied to the test data generation of programs.It is shown that our method outperforms the related methods in running time,success rate and stability.

Key words

software testing / path division / test data / path coverage / artificial fish-swarm algorithm

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LIAO Wei-zhi. Test Data Generation Based on Automatic Division of Path[J]. Acta Electronica Sinica, 2016, 44(9): 2254-2261. https://doi.org/10.3969/j.issn.0372-2112.2016.09.034

References

[1] 巩敦卫,张婉秋.基于自适应分组的大规模路径覆盖测试数据进化生成[J].控制与决策,2011,26(7):979-983. Gong Dunwei,Zhang Wanqiu.Evolutionary generation of test data for many paths coverage based on adaptive grouping[J].Control and Decision,2011,26(7):979-983.(in Chinese)
[2] 张婉秋.基于遗传算法的多路径覆盖测试数据生成方法[D].江苏徐州:中国矿业大学,2010. Zhang Wanqiu.Genetic algorithm based test data generation for multiple paths coverage[D].Xuzhou,Jiangsu:China University of Mining and Technology,2010.(in Chinese)
[3] Stefan J Galler,Bernhard K Aichernig.Survey on test data generation tools[J].International Journal on Software Tools for Technology Transfer,2014,16(6):727-751.
[4] Nigel Tracey,John Clark,Keith Mander.An automated framework for structural test-data generation[A].Proceedings of the International Conference on Automated Software Engineering[C].USA:IEEE,1998.285-285.
[5] Xiaofeng Xu,Yan Chen,Xiaochao Li.A path-oriented test data generation approach for automatic software testing[A].Proceedings of the 2nd International Conference on Anti-counterfeiting,Security and Identification[C].Piscataway:IEEE,2008.63-66.
[6] Eugenia Diaz,Javier Tuya,Raquel Blanco.A tabu search algorithm for structural software testing[J].Computers & Operations Research,2008,35(10):3052-3072.
[7] 胡岳峰,高建华.一种面向对象测试用例自动生成的混合算法[J].计算机应用研究,2008,25(3):786-788. Hu Yuefeng,Gao Jianhua.Hybrid algorithm of automatically generating of test data for object-oriented program[J].Application Research of Computers,2008,25(3):786-788.(in Chinese)
[8] Moataz A Ahmed,Irman Hermadi.GA-based multiple paths test data generator[J].Computers & Operations Research,2008,35(10):3107-3124.
[9] Paulo Marcos Siqueira Bueno,Mario Jino.Automatic test data generation for program paths using genetic algorithms[J].International Journal of Software Engineering and Knowledge Engineering,2002,12(6):691-709.
[10] Jin-Cherng Lin,Pu-Lin Yeh.Automatic data generation for path testing using Gas[J].Information Sciences,2001,131(1-4):47-64.
[11] 张岩,巩敦卫.基于搜索空间自动缩减的路径覆盖测试数据进化生成[J].电子学报,2012,40(5):1011-1016. Zhang Yan,Gong Dunwei.Evolutionary generation of test data for path coverage based on automatic reduction of search space[J].Acta Electronica Sinica,2012,40(5):1011-1016.(in Chinese)
[12] A A Sofokleous,A S Andreou.Automatic evolutionary test data generation for dynamic software testing[J].Journal of System and Software,2008,81(11):1883-1898.
[13] 谢晓园,徐宝文,史亮,聂长海.面向路径覆盖的演化测试用例生成技术[J].软件学报,2009,20(12):3117-3136. Xie Xiaoyuan,Xu Baowen,Shi Liang,Nie Changhai.Genetic test case generation for path-oriented testing[J].Journal of Software,2009,20(12):3117-3136.(in Chinese)
[14] Yong Chen,Yong Zhong.Automatic path-oriented test data generation using a multi-population genetic algorithm[A].Proceeding of the 4th International Conference on Natural Computation[C].Piscataway:IEEE Press,2008.565-570.
[15] Chengying Mao.Structural test data generation based on harmony search[J].Lecture Notes in Computer Science,2013.353-360.
[16] 李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式:鱼群算法[J].系统工程理论与实践,2002,22(11):32-38 Li Xiaolei,Shao Zhijiang,Qian Jixin.An optimizing method based on autonomous animats:fish-swarm algorithm[J].Systems Engineering-Theory & Practice,2002,22(11):32-38.(in Chinese)
[17] 王培崇,钱旭.基于改进鱼群算法的路径测试数据生成[J].计算机应用,2013,33(4):1139-1141. Wang Peichong,Qian Xu.Path test data generation based on improved artificial fish swarm algorithm[J].Journal of Computer Applications,2013,33(4):1139-1141.(in Chinese)
[18] JCB Ribeiro,MA Zenha-Rela,FFD Vega.Test case evolution and input domain reduction strategies for the evolutionary testing of object-oriented software[J].Information and Software Technology,2009,51(11):1534-1548.
[19] McMinn P.Evolutionary Search for test data in the presence of state behavior[D].Sheffied,England:University of Sheffied,2005.
[20] 王联国,洪毅.基于冯·诺依曼领域结构的人工鱼群算法[J].控制理论与应用,2010,27(6):775-780. Wang Lianguo,Hong Yi.Artificial fish-swarm algorithm based on Von Neuman neighborhood[J].Control Theory & Applications,2010,27(6):775-780.(in Chinese)

Funding

National Natural Science Foundation of China (No.61163012); Research Fund of Colleges and Universities in Guangxi Zhuang Autonomous Region (No.2013ZD040); Open Fund Project of Key Laboratory of Hybrid Computing and Integrated Circuit Design and Analysis of Guangxi Province (No.2012HCIC01)
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