Adaptive random testing through iterative partitioning revisited
Adaptive random testing through iterative partitioning revisited
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DOI：
10.1145/1188895.1188903
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发表时间：
2006-11
期刊：
影响因子：
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通讯作者：
Johannes Mayer;T. Chen;D. Huang
中科院分区：
文献类型：
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作者：
Johannes Mayer;T. Chen;D. Huang
最近，通过迭代分区的自适应随机测试（IP-ART）被提出作为一种比纯随机测试更有效的随机测试方法。除此之外，它应该与非常好的随机测试技术（即基于距离的自适应随机测试和限制随机测试）同样有效，而仅具有线性和二次运行时间。在本文中，研究了矩形输入域的宽度和高度的比率对各种自适应随机测试方法的有效性的影响。根据我们的发现，提出了 IP-ART 的改进版本。还针对输入域的各种宽度和高度比率分析了新方法的有效性。
Recently, Adaptive Random Testing through Iterative Partitioning (IP-ART) has been proposed as a random testing method that is more effective than pure Random Testing. Besides this, it is supposed to be equally effective as very good random testing techniques, namely Distance-Based Adaptive Random Testing and Restricted Random Testing, while only having between linear and quadratic runtime. In the present paper, it is investigated what influence the ratio of width and height of a rectangular input domain has on the effectiveness of various Adaptive Random Testing methods. Based on our findings, an improved version of IP-ART is proposed. The effectiveness of the new method is also analyzed for various ratios of width and height of the input domain.