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首页> 外文期刊>International Journal on Software Tools for Technology Transfer >A reasoning-based approach to dynamic domain reduction in test data generation
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A reasoning-based approach to dynamic domain reduction in test data generation

机译:基于推理的测试数据生成中动态域缩减的方法

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In this article, a new criterion, domain coverage, for white box testing is introduced. In search of the biggest subdomains for input variables exercising a given path, the variable domains are broken down into overlapping subregions in such a way that the resultant subregions either exercise or deviate from the path. To this aim, an incremental method is applied to detect the subregions, covering the longest subpaths from the start of the given path. The detected subdomain is further subdivided, and this process is repeated as far as the path is fully covered. If no subdomain is detected, the method is backtracked. The backtrack begins with the subdomain covering the longest subpath at the beginning of the given path, but this time the subdomain is divided into relatively smaller subregions, compared with the last time. A directed acyclic graph representation of each input variable domain is used to ignore re-examination of those subdomains which deviate from the path. Conducted experiments reveal that our proposed domain-oriented algorithm outperforms the existing path-oriented test data generation algorithms.
机译:在本文中,介绍了用于白盒测试的新标准域覆盖。为了寻找最大子域以寻找执行给定路径的输入变量,将变量域分解为重叠的子区域,以使所得子区域可以运动或偏离路径。为此,采用了一种增量方法来检测子区域,该子区域从给定路径的起点开始覆盖最长的子路径。将检测到的子域进一步细分,并重复此过程,直到完全覆盖路径为止。如果未检测到子域,则该方法将回溯。回溯从子域开始,该子域在给定路径的开头覆盖了最长的子路径,但是这次,与上次相比,该子域被划分为相对较小的子区域。每个输入变量域的有向无环图表示用于忽略那些偏离路径的子域的重新检查。进行的实验表明,我们提出的面向领域的算法优于现有的面向路径的测试数据生成算法。

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