输入代数

Rahul Gopinath, Hamed Nemati, A. Zeller
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引用次数: 3

摘要

基于语法的测试生成器在生成语法上有效的测试输入方面非常有效,并且使用户可以精确地控制应该生成哪些测试输入。但是,为特定的测试目标调整语法或测试生成器可能很乏味。我们引入语法转换器的概念,专门化语法以包含或排除特定模式:“电话号码不能以011或+1开头”。据我们所知,我们的方法是第一个允许任意布尔模式组合的方法,在创建目标软件测试时为测试人员提供了前所未有的灵活性。生成的专门化语法可以与任何基于语法的模糊器一起用于目标测试生成,但也可以作为验证器来检查给定的专门化是否得到满足,从而打开额外的使用场景。在我们对现实世界bug的评估中,我们展示了专门的语法在生成和验证目标输入时都是准确的。
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Input Algebras
Grammar-based test generators are highly efficient in producing syntactically valid test inputs, and give their user precise control over which test inputs should be generated. Adapting a grammar or a test generator towards a particular testing goal can be tedious, though. We introduce the concept of a grammar transformer, specializing a grammar towards inclusion or exclusion of specific patterns: "The phone number must not start with 011 or +1". To the best of our knowledge, ours is the first approach to allow for arbitrary Boolean combinations of patterns, giving testers unprecedented flexibility in creating targeted software tests. The resulting specialized grammars can be used with any grammar-based fuzzer for targeted test generation, but also as validators to check whether the given specialization is met or not, opening up additional usage scenarios. In our evaluation on real-world bugs, we show that specialized grammars are accurate both in producing and validating targeted inputs.
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