Experience report: Application of falsification methods on the UxAS system

Cumhur Erkan Tuncali, Bardh Hoxha, Guohui Ding, Georgios Fainekos, Sriram Sankaranarayanan

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

4 Scopus citations

Abstract

In this report, we present our experiences in applying falsification methods over the Unmanned Systems Autonomy Services (UxAS) system. UxAS is a collection of software modules that enables complex mission planning for multiple vehicles. To test the system, we utilized the tool S-TaLiRo to generate mission scenarios for both UxAS and the underlying vehicle simulators, with the goal of finding behaviors which do not meet system specifications.

Original languageEnglish (US)
Title of host publicationNASA Formal Methods 10th International Symposium, 10th International Symposium, NFM 2018 Newport News, Proceedings
PublisherSpringer Verlag
Pages452-459
Number of pages8
ISBN (Print)9783319779348
DOIs
StatePublished - Jan 1 2018
Event10th International Symposium on NASA Formal Methods, NFM 2018 - Newport News, United States
Duration: Apr 17 2018Apr 19 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10811 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Symposium on NASA Formal Methods, NFM 2018
CountryUnited States
CityNewport News
Period4/17/184/19/18

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Tuncali, C. E., Hoxha, B., Ding, G., Fainekos, G., & Sankaranarayanan, S. (2018). Experience report: Application of falsification methods on the UxAS system. In NASA Formal Methods 10th International Symposium, 10th International Symposium, NFM 2018 Newport News, Proceedings (pp. 452-459). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10811 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-77935-5_30