ITL Monitor: Compositional Runtime Analysis with Interval Temporal Logic
type: CreativeWork
description: Runtime verification has gained significant interest in recent years. It is a process in which the execution trace of a program is analysed while it is running. A popular language for specifying temporal requirements for runtime verification is Linear Temporal Logic (LTL), which is excellent for expressing properties such as safety and liveness. Another formalism that is used is Interval Temporal Logic (ITL). This logic has constructs for specifying the behaviour of programs that can be decomposed into subintervals of activity. Traditionally, only a restricted subset of ITL has been used for runtime verification due to the limitations imposed by making the subset executable. In this thesis an alternative restriction of ITL was considered as the basis for constructing a library of runtime verification monitors (ITL-Monitor). The thesis introduces a new first-occurrence operator (|>) into ITL and explores its properties. This operator is the basis of the translation from runtime monitors to their corresponding ITL formulae. ITL-Monitor is then introduced formally, and the algebraic properties of its operators are analysed. An implementation of ITL-Monitor is given, based upon the construction of a Domain Specific Language using Scala. The architecture of the underlying system comprises a network of concurrent actors built on top of Akka - an industrial strength distributed actor framework. A number of example systems are constructed to evaluate ITL-Monitor's performance against alternative verification tools. ITL-Monitor is also subjected to a simulation that generates a very large quantity of state data. The monitors were observed to deliver consistent performance across execution traces of up to a million states, and to verify subintervals of up to 300 states against ITL formulae with evaluation complexity of O(n^3).
abstract: Runtime verification has gained significant interest in recent years. It is a process in which the execution trace of a program is analysed while it is running. A popular language for specifying temporal requirements for runtime verification is Linear Temporal Logic (LTL), which is excellent for expressing properties such as safety and liveness. Another formalism that is used is Interval Temporal Logic (ITL). This logic has constructs for specifying the behaviour of programs that can be decomposed into subintervals of activity. Traditionally, only a restricted subset of ITL has been used for runtime verification due to the limitations imposed by making the subset executable. In this thesis an alternative restriction of ITL was considered as the basis for constructing a library of runtime verification monitors (ITL-Monitor). The thesis introduces a new first-occurrence operator (|>) into ITL and explores its properties. This operator is the basis of the translation from runtime monitors to their corresponding ITL formulae. ITL-Monitor is then introduced formally, and the algebraic properties of its operators are analysed. An implementation of ITL-Monitor is given, based upon the construction of a Domain Specific Language using Scala. The architecture of the underlying system comprises a network of concurrent actors built on top of Akka - an industrial strength distributed actor framework. A number of example systems are constructed to evaluate ITL-Monitor's performance against alternative verification tools. ITL-Monitor is also subjected to a simulation that generates a very large quantity of state data. The monitors were observed to deliver consistent performance across execution traces of up to a million states, and to verify subintervals of up to 300 states against ITL formulae with evaluation complexity of O(n^3).
author: Smallwood, David
license: https://dora.dmu.ac.uk/bitstreams/21d0f671-e006-4b4f-8171-c1b8d90e2e14/download
date published: 2019-05
date modified: 2026-07-24T06:18:42Z
provider: De Montfort University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: De Montfort University