Pattern Matching and Parameter Identification for Parametric Timed Regular Expressions

Akshay Mambakam, E. Asarin, Nicolas Basset, T. Dang
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引用次数: 0

Abstract

Timed formalisms such as Timed Automata (TA), Signal Temporal Logic (STL) and Timed Regular expressions (TRE) have been previously applied as behaviour specifications for monitoring or runtime verification, in particular, under the form of pattern-matching, i.e. computing the set of all the segments of a given system run that satisfy the specification. In this work, timed regular expressions with parameters (for timing delays and for signal values) are considered. We define several classes of parametric expressions (based on Boolean or real-valued signals and discrete events), and tackle the problem of computing a parametric match-set, i.e. the parameter values and time segments of data that give a match for a given expression. We propose efficient data structures for representing match-sets (combining zones and polytopes), and devise pattern-matching algorithms. All these different types and algorithms are combined into a single implementation under a tool named parameTRE. We illustrate the approach on several examples, from electrocardiograms to driving patterns.
参数定时正则表达式的模式匹配与参数识别
定时形式化,如定时自动机(TA)、信号时序逻辑(STL)和定时正则表达式(TRE),以前已经被应用于监控或运行时验证的行为规范,特别是在模式匹配的形式下,即计算给定系统运行中满足规范的所有部分的集合。在这项工作中,考虑了带参数的定时正则表达式(用于定时延迟和信号值)。我们定义了几类参数表达式(基于布尔值或实值信号和离散事件),并解决了计算参数匹配集的问题,即给定表达式的参数值和数据的时间片段。我们提出了表示匹配集的有效数据结构(结合区域和多面体),并设计了模式匹配算法。所有这些不同的类型和算法在一个名为parameterre的工具下组合成一个单独的实现。我们用几个例子来说明这种方法,从心电图到驾驶模式。
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