[1]刘冬[][],靳蓓蓓[],阙向红[]. 基于一种遗传算法的最小测试用例集自动生成[J].计算机技术与发展,2016,26(04):86-89.
　LIU Dong[][],JIN Bei-bei[],QUE Xiang-hong[]. Automatic Generation of Minimal Test Set Based on a Genetic Algorithm[J].,2016,26(04):86-89.
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 基于一种遗传算法的最小测试用例集自动生成()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年04期
页码:
86-89
栏目:
智能、算法、系统工程
出版日期:
2016-04-10

文章信息/Info

Title:
 Automatic Generation of Minimal Test Set Based on a Genetic Algorithm
文章编号:
1673-629X（2016)04-0086-04
作者:
 刘冬[1][2];  靳蓓蓓[3] ; 阙向红[2]
 1.皖南医学院第一附属医院 计算机中心；2. 华中科技大学 网络与计算中心；3.安徽师范大学
Author(s):
 LIU Dong[1][2] ; JIN Bei-bei[3];  QUE Xiang-hong[2]
关键词:
 ; 测试用例集; 测试用例; 基本路径集; 基本遗传算法; 软件测试
Keywords:
 ; test set; test case; basic path set; simple genetic algorithm; software testing
分类号:
TP301.6
文献标志码:
A
摘要:
 测试数据的生成是一个复杂的问题，且其技术和方法还不成熟。在生成最小测试用例集过程中，为了避免基本遗传算法对已经满足测试需求的测试用例重复进行遗传操作，文中在基本遗传算法的基础上，最大提高遗传算法的稳定性，提出最大稳定遗传算法( LSGA)。该算法能很好地保证种群的最大稳定性，提高搜索性能，最后对该算法从概率角度理论证明其优越性。实例分析表明，利用该算法能较快生成最小测试用例集，从而实现对测试目标的充分测试，提高测试效率，降低测试成本。
Abstract:
 Test data generation is a complicated problem and its method and technique is not mature. In the process of the minimum test case generation,the Largest Steady Genetic Algorithm ( LSGA) is proposed to improve the stability greatly,which is based on the basic genetic algorithm,in order to avoid repeat genetic manipulation of test case which has been met the testing requirement. This algorithm can guarantee the largest population stability and improve the search performance. Contrasted with the genetic algorithm,its superiority is proved from the perspective of the probability. Example analysis shows that using the proposed algorithm can rapidly generate minimum test case sets,achieving the target of the full test,improving the test efficiency and reducing test cost.

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更新日期/Last Update: 2016-06-16