Fast falsification of hybrid systems using probabilistically adaptive input

Gidon Ernst, Sean Sedwards, Zhenya Zhang, Ichiro Hasuo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We present an algorithm that quickly finds falsifying inputs for hybrid systems, i.e., inputs that steer the system towards violation of a given temporal logic requirement. Our method is based on a probabilistically directed search of an increasingly fine grained spatial and temporal discretization of the input space. A key feature is that it adapts to the difficulty of a problem at hand, specifically to the local complexity of each input segment, as needed for falsification. In experiments with standard benchmarks, our approach shows comparable or better performance to existing techniques, while at the same time being relatively simple.

Original languageEnglish
Title of host publicationQuantitative Evaluation of Systems - 16th International Conference, QEST 2019, Proceedings
EditorsDavid Parker, Verena Wolf
PublisherSpringer Verlag
Pages165-181
Number of pages17
ISBN (Print)9783030302801
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event16th International Conference on Quantitative Evaluation of Systems, QEST 2019 - Glasgow, United Kingdom
Duration: Sep 10 2019Sep 12 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11785 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Quantitative Evaluation of Systems, QEST 2019
CountryUnited Kingdom
CityGlasgow
Period9/10/199/12/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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