首页> 外国专利> METHOD FOR AUTOMATICALLY GENERATING SEARCH HEURISTICS AND PERFORMING METHOD OF CONCOLIC TESTING USING AUTOMATICALLY GENERATED SEARCH HEURISTICS

METHOD FOR AUTOMATICALLY GENERATING SEARCH HEURISTICS AND PERFORMING METHOD OF CONCOLIC TESTING USING AUTOMATICALLY GENERATED SEARCH HEURISTICS

机译:自动生成搜索启发式的方法和使用自动生成搜索启发式进行隐式测试的方法

摘要

An automatic generation method of a search strategy used in concurrency testing for a target program according to the present invention includes: (a) generating feature vectors corresponding to branch statements included in the target program, and each dimension of the feature vectors Initializing sample spaces corresponding to, (b) randomly generating first parameter vectors having the same dimensions as the feature vectors, and including components selected from the sample spaces, (c) the object Selecting second parameter vectors among the first parameter vectors based on the size of the first branch statement coverage of each of the first parameter vectors for the program, (d) the second parameter vector for the target program Individually reducing the sample spaces based on the average branch statement coverage of each of the (e) the second parameter Repeatedly performing steps (b) to (d) so that the average branch statement coverage of some of the vectors converges to the maximum, and (f) when the average branch statement coverage converges to the maximum, the maximum average branch And outputting an optimal parameter vector corresponding to the door coverage, but when step (b) is repeatedly performed, components of each of the first parameter vectors are individually reduced sample spaces in step (d). Can be selected from.
机译:根据本发明的在并发测试中用于目标程序的搜索策略的自动生成方法,包括:(a)生成与目标程序中包括的分支语句相对应的特征向量,以及特征向量的各个维度,初始化与之对应的样本空间。 ;(b)随机生成与特征向量具有相同尺寸并且包括从样本空间中选择的分量的第一参数向量;(c)对象根据第一分支的大小从第一参数向量中选择第二参数向量程序的每个第一参数向量的语句覆盖率,(d)目标程序的第二参数向量的覆盖率,基于(e)第二参数中每个参数的平均分支语句覆盖率,分别减少样本空间。重复执行步骤( b)至(d),以使某些向量的平均分支语句覆盖率收敛到最大值, (f)当平均分支语句覆盖率收敛到最大值时,最大平均分支并输出与门覆盖率相对应的最优参数向量,但是当重复执行步骤(b)时,每个第一参数向量的分量为在步骤(d)中分别减少样本空间。可以选择。

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