Falsification of cyber-physical systems with robustness uncertainty quantification through stochastic optimization with adaptive restart

Logan Mathesen, Shakiba Yaghoubi, Giulia Pedrielli, Georgios Fainekos

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

1 Scopus citations

Abstract

This work is in the field of requirements driven search-based test case generation methods for Cyber-Physical Systems (CPS). The basic characteristic of search-based testing methods is that the search process is guided by high level requirements captured in formal logic and, in particular, Signal Temporal Logic (STL). Given a system trajectory, STL specifications can be equipped with quantitative semantics which evaluate the closeness of the given trajectory from violating the requirement. Hence, by searching for trajectories of decreasing value with respect to the specification, a test generation method can be formulated which searches for system behaviors with a closeness to violation value of less than 0. These system behaviors, i.e., trajectories that violate the requirements and yield STL closeness value less than 0, are referred to as falsiping behaviors. In addition, signed distance can be utilized when searching for trajectories that maximally violate the specification (negative specification valuations). In this work, we propose the use of a stochastic search method that mixes global and local search for system test case generation. The implemented search method models input-output relationships between test cases and the observed STL closeness values of the yielded system trajectories, adaptively linking input-out of both global and local regional modeling. The method shows improved finite time performance, i.e., quick identification of falsification behaviors, over current search-based test case generation methods. Further, given no falsifying behaviors are found in finite time our method is capable of quantifying the certainty that no falsifying behaviors exist.

Original languageEnglish (US)
Title of host publication2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019
PublisherIEEE Computer Society
Pages991-997
Number of pages7
ISBN (Electronic)9781728103556
DOIs
StatePublished - Aug 2019
Event15th IEEE International Conference on Automation Science and Engineering, CASE 2019 - Vancouver, Canada
Duration: Aug 22 2019Aug 26 2019

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2019-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference15th IEEE International Conference on Automation Science and Engineering, CASE 2019
CountryCanada
CityVancouver
Period8/22/198/26/19

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Keywords

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Mathesen, L., Yaghoubi, S., Pedrielli, G., & Fainekos, G. (2019). Falsification of cyber-physical systems with robustness uncertainty quantification through stochastic optimization with adaptive restart. In 2019 IEEE 15th International Conference on Automation Science and Engineering, CASE 2019 (pp. 991-997). [8843005] (IEEE International Conference on Automation Science and Engineering; Vol. 2019-August). IEEE Computer Society. https://doi.org/10.1109/COASE.2019.8843005