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Rewriting-Based Techniques for Runtime Verification

机译:基于重写的运行时验证技术

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Techniques for efficiently evaluating future time Linear Temporal Logic (abbreviated LTL) formulae on finite execution traces are presented. While the standard models of LTL are infinite traces, finite traces appear naturally when testing and/or monitoring real applications that only run for limited time periods. A finite trace variant of LTL is formally defined, together with an immediate executable semantics which turns out to be quite inefficient if used directly, via rewriting, as a monitoring procedure. Then three algorithms are investigated. First, a simple synthesis algorithm for monitors based on dynamic programming is presented; despite the efficiency of the generated monitors, they unfortunately need to analyze the trace backwards, thus making them unusable in most practical situations. To circumvent this problem, two rewriting-based practical algorithms are further investigated, one using rewriting directly as a means for online monitoring, and the other using rewriting to generate automata-like monitors, called binary transition tree finite state machines (and abbreviated BTT-FSMs). Both rewriting algorithms are implemented in Maude, an executable specification language based on a very efficient implementation of term rewriting. The first rewriting algorithm essentially consists of a set of equations establishing an executable semantics of LTL, using a simple formula transforming approach. This algorithm is further improved to build automata on-the-fly via caching and reuse of rewrites (called memoization), resulting in a very efficient and small Maude program that can be used to monitor program executions. The second rewriting algorithm builds on the first one and synthesizes provably minimal BTT-FSMs from LTL formulae, which can then be used to analyze execution traces online without the need for a rewriting system. The presented work is part of an ambitious runtime verification and monitoring project at NASA Ames, called PATHEXPLORER, and demonstrates that rewriting can be a tractable and attractive means for experimenting and implementing logics for program monitoring.
机译:提出了有效地评估有限执行轨迹上的未来时间线性时序逻辑(缩写为LTL)公式的技术。虽然LTL的标准模型是无限跟踪,但是当测试和/或监视仅在有限时间段内运行的实际应用程序时,自然就会出现有限跟踪。正式定义了LTL的有限跟踪变体以及直接可执行的语义,如果直接通过重写将其用作监视过程,则效率非常低。然后研究了三种算法。首先,提出了一种基于动态规划的监视器综合简单算法。尽管生成的监视器效率很高,但不幸的是,它们仍需要向后分析轨迹,从而使它们在大多数实际情况下不可用。为了解决这个问题,我们进一步研究了两种基于重写的实用算法,一种直接使用重写作为在线监视的手段,另一种使用重写生成类似自动机的监视器,称为二进制过渡树有限状态机(缩写为BTT- FSM)。两种重写算法均在Maude中实现,Maude是一种基于术语重写非常有效的实现的可执行规范语言。第一种重写算法实质上由一组方程式组成,这些方程式使用简单的公式转换方法来建立LTL的可执行语义。对该算法进行了进一步改进,以通过缓存和重用重写(称为备忘录)来即时构建自动机,从而生成了一个非常有效的小型Maude程序,可以用来监视程序执行。第二种重写算法以第一种重写算法为基础,并从LTL公式合成了可证明的最小BTT-FSM,然后可以将其用于在线分析执行跟踪,而无需重写系统。呈现的工作是NASA Ames一项雄心勃勃的运行时验证和监视项目PATHEXPLORER的一部分,并演示了重写可以成为试验和实现程序监视逻辑的一种吸引人的有吸引力的方式。

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