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基于量子遗传算法的软件测试数据自动生成 被引量:8

Automatically Generate Software Test Data Based on Quantum Genetic Algorithm
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摘要 测试数据的自动生成是测试阶段最关键的技术问题,改进软件测试方法,对提高软件测试的自动化程度具有十分重要的现实意义;在测试数据的自动生成的方法中,遗传算法虽然取得了较好的效果,但是这种算法存在缺陷和局限性,而量子遗传算法改善了其不足之处;应用量子遗传算法解决软件测试数据生成问题,克服了传统的以测试数据为核心的测试方法的不足和缺陷,实验结果表明量子遗传算法的测试用例生成效率高于遗传算法;所以,量子遗传算法可以作为一种较为理想的算法进行测试数据的自动生成,对软件测试中的测试数据自动生成具有很强的使用价值。 Quantum genetic algorithm is applied to solve software test data generation problem, in order to overcome the traditional deficiencies and defects. Experimental results show that the quantum genetic algorithm to generate the test cases is more efficient than genetic algorithms. Therefore, quantum genetic algorithm can be used as an ideal algorithm for automatic generation of test data for software testing.
出处 《计算机测量与控制》 CSCD 北大核心 2010年第1期34-37,共4页 Computer Measurement &Control
关键词 软件测试 量子遗传算法 遗传算法 测试数据 software testing quantum genetic algorithm genetic algorithm test data
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参考文献14

  • 1Sun J, Feng B, Xu W B. Particle Swarm Optimization with Particles Having Quantum Behavior [A]. Proceedings of 2004 Congress on Evolutionary Computation [C]. 2004, 325-331.
  • 2Jones B, Sthamer H, Eyres D. Automatic structural testing using genetic algorithms [J].Software Engineering Journal, 1996, 11 (5): 299-306.
  • 3Sthamer H H. l'he automatic generation of software test data USing genetic algorithms[D]. Wales~ University of Glamorgan, Pontyprido 1996: 300-309.
  • 4Tracey N, Clark J, Mander K. An automated framework for structural test data generation [A].Proe of the 13th IEEE Conference on Automated Software Engineering [C]. Hawaii, USA, 1998: 285-288.
  • 5IAn J C, Yeh PI _ Using genetic algorithms for test ciKse goneration in path testing [A]. Proc of the Asian Test symposium [C]. 2000: 241-246.
  • 6Akyildiz F, Su W, Sanakamaniam Y. Wireless sensor networks: A survey[J]. 1EEEComputerNetworks, 2002, 38 (4): 393 -422.
  • 7Hermadi I, Ahmed M A. Genetic algorithm based on test datagenerator [A]. CEC' 03 [C]. 2003: 85-91.
  • 8Han K H, Park K H, Lee C H, et al. Parallel quantum-inspired genetic algorithm for combinatorial optimization problem [ A]. Proc, Congress on Evolutionary Computation [C]. Seoul, Korea.
  • 9Kim K H, Hwang J Y, Han K H, et al. A Quantum-inspired evolutionary computing algorithm for disk allocation method [J]. IEICE Trans. Inform. Syst. , vol. E86-D, pp. 645-649, Mar. 2003.
  • 10林闯.多媒体信息网络QoS的控制[J].软件学报,1999,10(10):1016-1024. 被引量:44

二级参考文献33

  • 1奚红宇,徐红,高仲仪.Ada软件测试用例生成工具[J].软件学报,1997,8(4):297-302. 被引量:6
  • 2荚伟,高仲仪.基于遗传算法的软件结构测试数据生成技术研究[J].北京航空航天大学学报,1997,23(1):36-40. 被引量:14
  • 3Shooman M.Software Engineering : Design, Reliability and Management [M].MeGraw-Hill, 1983.
  • 4Chellappa M.Nontraversible Paths in a Program[J].IEEE Transactions on Software Engineering, 1987; 13(6) :751-756.
  • 5Bertolino A.Unconstrained Edges and Their Application to Branch Analysis and Testing of Progranm[J].The Journal of Systems and Software, 1993 ;20(2) : 125-133.
  • 6Bertolino A,Marré M.How Many Paths are Needed for Branch Testing?[J].The Journal of Systems and Software, 1996;35(2) :95-106.
  • 7Bertolino A,Marré M.Automatic Generation of Path Covers Based on the Control Flow Analysis of Computer Programs[J].IEEE Transactions on Software Engineering, 1994 ;20 (12) : 885-899.
  • 8Bertolino A,Mirandola R,Peciola E.A Case Study in Branch Testing Automation[J].The Journal of Systems and Software, 1997 ;38 ( 1 ) :47-59.
  • 9Andrews M,Proc 18th Annual Joint Conference of the IEEE Computer and Communications Societies(IEEE INFOCOM’99),1999年,380页
  • 10Chang C S,Proc 18th Annual Joint Conference of the IEEE Computer and Communications Societies(IEEE INFOCOM’99),1999年,63页

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