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arXiv 2203.07982cs.LOcs.AI
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数据感知动态系统的线性时间算法验证

Linear-Time Verification of Data-Aware Dynamic Systems with Arithmetic

Free University of Bozen-Bolzano(博尔扎诺自由大学)

Paolo Felli, Marco Montali, Sarah Winkler

摘要:

动态系统及其操作数据的组合建模和验证在人工智能和多个应用领域中获得了发展势头。我们研究了数据感知动态系统(DDS)的表达而简洁的框架,用线性算法对其进行了扩展,并提供了以下贡献。首先,我们引入了一个新的,语义属性的“有限总结”,这保证了一个忠实的有限状态抽象的存在。我们依靠这一点来证明,检查证人是否存在的线性时间,有限跟踪属性是可判定的DDS有限总结。第二,我们证明了在形式化方法和数据库理论中研究的几个可判定性条件可以被看作是这个属性的具体的、可检查的实例。这也产生了新的可判定性结果。第三,我们展示了如何抽象的,统一的属性有限总结导致模块化的结果:一个系统享有有限总结,如果它可以被适当地划分成更小的系统,拥有的财产。我们的研究结果使我们能够分析在早期方法中无法实现的系统。最后,我们证明了我们的方法在原型实现的可行性。

英文摘要:

Combined modeling and verification of dynamic systems and the data they operate on has gained momentum in AI and in several application domains. We investigate the expressive yet concise framework of data-aware dynamic systems (DDS), extending it with linear arithmetic, and provide the following contributions. First, we introduce a new, semantic property of "finite summary", which guarantees the existence of a faithful finite-state abstraction. We rely on this to show that checking whether a witness exists for a linear-time, finite-trace property is decidable for DDSs with finite summary. Second, we demonstrate that several decidability conditions studied in formal methods and database theory can be seen as concrete, checkable instances of this property. This also gives rise to new decidability results. Third, we show how the abstract, uniform property of finite summary leads to modularity results: a system enjoys finite summary if it can be partitioned appropriately into smaller systems that possess the property. Our results allow us to analyze systems that were out of reach in earlier approaches. Finally, we demonstrate the feasibility of our approach in a prototype implementation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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