Empirical evaluation of a nesting testability transformation for evolutionary testing
Empirical evaluation of a nesting testability transformation for evolutionary testing
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DOI：
10.1145/1525880.1525884
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发表时间：
2009-05
期刊：
影响因子：
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通讯作者：
Phil McMinn;D. Binkley;M. Harman
中科院分区：
文献类型：
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作者：
Phil McMinn;D. Binkley;M. Harman
进化测试是一种自动生成测试数据的方法，它使用进化算法在测试对象的输入域中搜索测试数据。嵌套谓词可能会导致进化测试出现问题，因为指导搜索所需的信息只有在满足每个嵌套条件时才可用。这意味着搜索过程可能会过度适应早期信息，从而使满足在搜索后期才变得明显的约束变得更加困难，有时甚至几乎不可能。本文提出了一种可测试性转换，允许同时评估所有嵌套条件。提出了两项实证研究。第一项研究表明，嵌套处理的形式在实践中很普遍。第二项研究展示了该方法如何改进进化测试数据的生成。
Evolutionary testing is an approach to automating test data generation that uses an evolutionary algorithm to search a test object's input domain for test data. Nested predicates can cause problems for evolutionary testing, because information needed for guiding the search only becomes available as each nested conditional is satisfied. This means that the search process can overfit to early information, making it harder, and sometimes near impossible, to satisfy constraints that only become apparent later in the search. The article presents a testability transformation that allows the evaluation of all nested conditionals at once. Two empirical studies are presented. The first study shows that the form of nesting handled is prevalent in practice. The second study shows how the approach improves evolutionary test data generation.