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基于遗传算法的测试用例生成技术研究

Study on Test Case Automated Generation Technology Based on Genetic Algorithm

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【作者】 吴云; 胡小娟; 邱宁佳; 王鹏; 杨华民;

【Author】 WU Yun1,HU Xiaojuan2,QIU Ningjia2,WANG Peng2,YANG Huamin2 (1.Mathematical Sciences,Baotou Teachers College,BaoTou 014030; 2.School of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022)

【机构】 包头师范学院数学科学学院; 长春理工大学计算机科学技术学院;

【摘要】 提出了一种结合遗传算法和神经网络算法的测试用例生成方法,算法融合了误差反向传播算法在避免陷入局部最优和保持种群多样性方面的优势,克服了遗传算法局部搜索能力差及其早熟现象。实验结果表明,新方法在测试用例自动生成的效率和效果方面,优于传统遗传算法。

【Abstract】 In the software testing technology,efficient test case generation is a means for simplifying the testing work, and improving the efficiency of the test.A newly kind of software test case automated generation method based on genetic algorithm and neural network algorithm is proposed.The algorithm combines genetic algorithm with back propagation algorithm to overcome the disadvantages of local optimum and keep the advantages of species diversity.The experiment results show that this algorithm is superior to the traditional genetic algorithm in efficiency and effectiveness of test case generation.

  • 【文献出处】 长春理工大学学报(自然科学版) ,Journal of Changchun University of Science and Technology(Natural Science Edition) , 编辑部邮箱 ,2010年03期
  • 【分类号】TP311.53
  • 【被引频次】5
  • 【下载频次】183
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