Property Directed Generation of First-Order Test Data
Property Directed Generation of First-Order Test Data
复制标题
一阶测试数据的属性定向生成
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Fredrik Lindblad
中科院分区：
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作者：
Fredrik Lindblad
随机测试是验证程序性质的一种有效方法。但是，随着程序和属性复杂性的增加，编写自定义的输入数据生成器变得非常必要。我们提出了一种方法，系统地生成输入数据的惰性实例化使用Meta变量和并行部分评估的属性。这适用于基于规范的程序验证。我们声称，一些程序验证问题可以通过系统生成而无需编写自定义生成器来处理，并且有些问题，对于这些问题，编写生成器不是一个解决方案，随机测试失败，仍然足够简单，可以用于系统生成。我们提出的系统是与功能逻辑编程。
Random testing is a powerful method for verifying program properties. However, as the complexity of the program and properties increases, writing customized input data generators quickly becomes necessary. We present a method for systematic generation of input data by lazy instantiation using meta variables and parallel partial evaluation of properties. This is applied on specification based program verification. We claim that some program verification problems can be handled by systematic generation without the need of writing custom generators, and that some problems, for which writing generators is not a solution and random testing fails, are still simple enough for systematic generation. The system we present is related to functional logic programming.