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蚁群模拟退火算法在测试用例约简中的应用 被引量:7

Application of Ant Simulated Annealing Algorithm in Test Case Reduction
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摘要 参数的成对组合覆盖测试技术是软件测试中有效的测试方法之一。该文将模拟退火思想引入蚁群算法,组成新的混合算法,即蚁群模拟退火混合算法(ASA),应用在组合测试用例的约简过程中。按照测试的特殊需求进行多种建模尝试,通过仿真实验对算法涉及的参数进行研究,实验验证了ASA算法对测试用例集的约简作用是有效的。 The technology of pair-wise covering test with parameters is an effective way in the software test. This paper proposes a mixed algorithm with Ant Colony Optimization algorithm(ACO) and Simulated Annealing algorithm(SA) which is called ASA for short, and uses it in pair-wise test case reduction. According to the special requirements, the paper attempts to process various modeling ways, and does the research on the parameters referring to this algorithm. The ASA algorithm is verified by the experiment, which indicates that the algorithm is effective in the reduction of the test case.
出处 《计算机工程》 CAS CSCD 北大核心 2009年第2期197-199,共3页 Computer Engineering
基金 四川省科技攻关计划基金资助项目“软件自动测试技术研究与自动测试工具开发”(05GG021-003-2) 科技部科技型中小企业技术创新基金资助项目“软件自动测试工具WsSTKit”(0626225101730)
关键词 成对组合覆盖测试 蚁群算法 模拟退火算法 测试用例约简 pair-wise covering test Ant Colony Optimization algorithm(ACO) Simulated Annealing algorithm(SA) test case reduction
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参考文献4

  • 1同济大学应用数学系.高等数学[M].5版.北京:高等教育出版社,2004.
  • 2章春芳,陈崚,陈娟.用自适应的多种群蚁群算法求解频率分配问题[J].计算机应用,2005,25(7):1641-1644. 被引量:6
  • 3Li Baolin, Li Zhishu, Zhang Jingyu, et al, An Automated Test Case Generation Approach by Genetic Simulated Annealing Algorithm[C]//Proc. of the 3rd International Conference on Natural Computation. Haikou, China: [s. n.], 2007:106-111.
  • 4Cohen D M, Dalai S R. The AETG System: An Approach to Testing Based on Combinatorial Design[J]. IEEE Transaction on Software Engineering, 1997, 23(7): 437-444.

二级参考文献14

  • 1童庆,曹先彬,钱海,王煦法.用于频率分配的免疫应答求解策略[J].小型微型计算机系统,2003,24(1):114-117. 被引量:5
  • 2刘根泉,王树禾,肖国龙.频率分配与图的着色[J].电子学报,1994,22(1):38-46. 被引量:17
  • 3GAMST A. Homogeneous distribution of frequencies in a regular hexagonal cell system[J]. IEEE Transactions on Vehicle Technology, 1982, VT-31(5):132 - 144.
  • 4MIDDENDORF M,REISCHLE F,SCHMECK H. Multi colony ant algorithms[J]. Heuristics, 2002, 8(3):305 - 320.
  • 5BLUM C, DORIGO M. The Hyper-Cube framework for ant colony optimization[J]. IEEE Transactions on SMC, 2004, 34(2): 1161- 1172.
  • 6PROSSER P. Hybrid algorithm for the constraint satisfaction problem[J]. Computational Intelligence, 1993, 9(3):268 - 297.
  • 7HALE WK. New spectrum management tools[A]. Proceedings of IEEE International Symposium on Eleltrornatic Compatibility Record[C], 1981.47-53.
  • 8DUQUE-ANTON M, KUNZ D, RUBER B. Channel assignment for cellular radio using simulated annealing[J].IEEE Transactions on Vehicular Technol, 1993,42(1): 14-21.
  • 9HURLEY S, SMITH DH. Fixed spectrum frequency assignment using natural algorithms[A]. Proceedings of the First Conference on Genetic Algorithms in Engineering Systems[C],1995. 373 -378.
  • 10LOCHTIE GD, MEHLER MJ. Channel assignment using a subspace approach to neural networks[A]. IEE Conference Publication[C],1995, 407. 296 -300.

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