概率自适应随机检验

Kwok-Ping Chan, T. Chen, D. Towey
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引用次数: 8

摘要

自适应随机测试(ART)方法是基于随机测试的软件测试方法,但它使用额外的机制来确保在输入域上测试用例的更均匀和更广泛的分布。限制性随机测试(RRT)是ART的一个版本,它使用排除区域并将测试用例生成限制在这些区域之外。RRT已经被发现执行得非常好,但是它对严格排除区域的使用(从其中不能生成测试用例)促使了对修改RRT方法的可能性的调查,这样在整个算法的持续时间内,输入域的所有部分仍然可用于测试用例的生成。在本文中,我们提出了一种概率方法,即概率ART (PART),并解释了两种不同的实现。初步的实证数据支持的方法也进行了审查
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Probabilistic Adaptive Random Testing
Adaptive random testing (ART) methods are software testing methods which are based on random testing, but which use additional mechanisms to ensure more even and widespread distributions of test cases over an input domain. Restricted random testing (RRT) is a version of ART which uses exclusion regions and restricts test case generation to outside of these regions. RRT has been found to perform very well, but its use of strict exclusion regions (from within which test cases cannot be generated) has prompted an investigation into the possibility of modifying the RRT method such that all portions of the input domain remain available for test case generation throughout the duration of the algorithm. In this paper, we present a probabilistic approach, probabilistic ART (PART), and explain two different implementations. Preliminary empirical data supporting the methods is also examined
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