基于改进蚁群算法的软件回归测试用例集优化方法  

Software Regression Test Case Set Optimization Method Based on Improved Ant Colony Algorithm

作　　者：刘汀 LIU Ting(Construction Information Technology Research Center of CMCU Engineering Co.,Ltd.,Chongqing 400039,China)

机构地区：[1]中机中联工程有限公司建筑信息技术研究中心,重庆400039

出　　处：《信息与电脑》2023年第2期84-86,共3页Information & Computer

摘　　要：为控制测试用例集合的冗余数据量,引进改进蚁群算法,设计针对软件回归测试的用例集优化方法。首先,建立测试用例集覆盖模型,掌握测试用例集数据信息的覆盖情况;其次,根据事件发生概率模型,以测试用例集的用例个数最小为优化目标,建立用例集优化目标函数;最后,在保证用例集满足要求的条件下,逐步缩小用例集信息的覆盖度,实现对测试用例集冗余信息的优化处理。实验结果证明,该方法可在最短迭代次数下使测试用例集达到最优,降低优化处理后测试用例集的冗余数据量。In order to control the redundant data of the test case set,an improved ant colony algorithm is introduced to design a case set optimization method for software regression testing.Firstly,establish a test case set coverage model to master the coverage of data information in the test case set.Secondly,according to the event probability model,the objective function of case set optimization is established with the minimum number of cases in the test case set as the optimization objective.Finally,under the condition of ensuring that the use case set meets the requirements,gradually reduce the coverage of the information in the use case set,and optimize the redundant information in the test case set.The experimental results show that this method can optimize the test case set in the shortest number of iterations,and reduce the amount of redundant data in the optimized test case set.

关 键 词：改进蚁群算法 目标函数 覆盖模型 优化方法 用例集 软件回归测试 

分 类 号：TP311.5[自动化与计算机技术—计算机软件与理论] TP301.6[自动化与计算机技术—计算机科学与技术]