基于多排序逻辑的高效数据模型验证

Ivan Bocic, T. Bultan
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引用次数: 6

摘要

在当今面向Internet的世界中,滥用或丢失web应用程序数据可能会造成灾难性的后果。因此,验证web应用程序数据模型是至关重要的。我们开发了一个框架,通过转换到一阶逻辑(FOL)来验证web应用程序数据模型,然后进行自动定理证明。由于FOL的不可判定性,这种自动化方法并不总是产生结论性的答案。在本文中,我们研究了多排序逻辑在数据模型验证中的使用,以提高该方法的有效性。多排序逻辑允许我们显式地指定类型信息,从而减轻了定理证明过程中关于类型信息的推理负担。我们的实验表明,使用多排序逻辑显著提高了验证性能,并且在超过7个真实web应用程序的所有情况下完全消除了不确定的结果,低于17%的不确定率。
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Efficient Data Model Verification with Many-Sorted Logic (T)
Misuse or loss of web application data can have catastrophic consequences in today's Internet oriented world. Hence, verification of web application data models is of paramount importance. We have developed a framework for verification of web application data models via translation to First Order Logic (FOL), followed by automated theorem proving. Due to the undecidability of FOL, this automated approach does not always produce a conclusive answer. In this paper, we investigate the use of many-sorted logic in data model verification in order to improve the effectiveness of this approach. Many-sorted logic allows us to specify type information explicitly, thus lightening the burden of reasoning about type information during theorem proving. Our experiments demonstrate that using many-sorted logic improves the verification performance significantly, and completely eliminates inconclusive results in all cases over 7 real world web applications, down from an 17% inconclusive rate.
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