计算机科学 ›› 2017, Vol. 44 ›› Issue (6): 177-181.doi: 10.11896/j.issn.1002-137X.2017.06.030
包晓安,杨亚娟,张娜,林青霞,俞成海
BAO Xiao-an, YANG Ya-juan, ZHANG Na, LIN Qing-xia and YU Cheng-hai
摘要： 最小覆盖表生成是组合测试研究的关键问题。基于演化搜索的粒子群算法在生成覆盖表时能得到较优的结果,但其性能受配置参数的影响。针对此问题,将one-test-at-a-time策略和自适应粒子群算法相结合,以种群粒子优劣为依据对惯性权重进行自适应调整,使其在覆盖表生成上具有更强的适用能力。为进一步提升算法性能,构造了一个优先级度量函数用于度量每个组合的权值,优先选取权值最高的组合用于单条测试用例的生成。最后,编程实现该算法,并将其与原有粒子群算法在组合测试用例集生成上展开对比性实验分析,结果证实该算法在规模和执行时间上具有竞争力。
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