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Falsification of Hybrid Systems Using Adaptive Probabilistic Search

Published: 18 July 2021 Publication History

Abstract

We present and analyse an algorithm that quickly finds falsifying inputs for hybrid systems. Our method is based on a probabilistically directed tree search, whose distribution adapts to consider an increasingly fine-grained discretization of the input space. In experiments with standard benchmarks, our algorithm shows comparable or better performance to existing techniques, yet it does not build an explicit model of a system. Instead, at each decision point within a single trial, it makes an uninformed probabilistic choice between simple strategies to extend the input signal by means of exploration or exploitation. Key to our approach is the way input signal space is decomposed into levels, such that coarse segments are more probable than fine segments. We perform experiments to demonstrate how and why our approach works, finding that a fully randomized exploration strategy performs as well as our original algorithm that exploits robustness. We propose this strategy as a new baseline for falsification and conclude that more discriminative benchmarks are required.

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Published In

cover image ACM Transactions on Modeling and Computer Simulation
ACM Transactions on Modeling and Computer Simulation  Volume 31, Issue 3
Special Issue on Qest 2019
July 2021
149 pages
ISSN:1049-3301
EISSN:1558-1195
DOI:10.1145/3476822
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 18 July 2021
Accepted: 01 March 2021
Revised: 01 November 2020
Received: 01 May 2020
Published in TOMACS Volume 31, Issue 3

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Author Tags

  1. Falsification
  2. hybrid systems
  3. principled probabilistic search

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  • (2024)Testing cyber-physical systems with explicit output coverage2024 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW60967.2024.00036(128-136)Online publication date: 27-May-2024
  • (2024)BEACON: A Bayesian Evolutionary Approach for Counterexample Generation of Control SystemsIEEE Access10.1109/ACCESS.2024.343651512(106455-106465)Online publication date: 2024
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  • (2022)Adaptive testing for specification coverage and refinement in CPS modelsNonlinear Analysis: Hybrid Systems10.1016/j.nahs.2022.10125446(101254)Online publication date: Nov-2022

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