research-article

Automated testing of hybrid Simulink/Stateflow controllers: industrial case studies

Authors:

Reza Matinnejad,

Shiva Nejati,

Lionel C. BriandAuthors Info & Claims

ESEC/FSE 2017: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

Pages 938 - 943

https://doi.org/10.1145/3106237.3117770

Published: 21 August 2017 Publication History

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Abstract

We present the results of applying our approach for testing Simulink controllers to one public and one proprietary model, both industrial. Our approach combines explorative and exploitative search algorithms to visualize the controller behavior over its input space and to identify test scenarios in the controller input space that violate or are likely to violate the controller requirements. The engineers' feedback shows that our approach is easy to use in practice and gives them confidence about the behavior of their models.

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Le Tolguenec PRachelson EBesse YTeichteil-Koenigsbuch FSchneider NWaeselynck HWilson DChristakis MPradel M(2024)Exploration-Driven Reinforcement Learning for Avionic System Fault Detection (Experience Paper)Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3650212.3680331(920-931)Online publication date: 11-Sep-2024
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Ayoughi NNejati SSabetzadeh MSaavedra PEgyed AWimmer MChechik MCombemale B(2024)Enhancing Automata Learning with Statistical Machine Learning: A Network Security Case StudyProceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems10.1145/3640310.3674087(172-182)Online publication date: 22-Sep-2024
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Luitel DNejati SSabetzadeh M(2024)Requirements-Driven Slicing of Simulink Models using LLMs2024 IEEE 32nd International Requirements Engineering Conference Workshops (REW)10.1109/REW61692.2024.00014(72-82)Online publication date: 24-Jun-2024
https://doi.org/10.1109/REW61692.2024.00014
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Index Terms

Automated testing of hybrid Simulink/Stateflow controllers: industrial case studies
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation

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Published In

ESEC/FSE 2017: Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

August 2017

1073 pages

ISBN:9781450351058

DOI:10.1145/3106237

General Chairs:
Eric Bodden
Paderborn University, Germany / Fraunhofer IEM, Germany
,
Wilhelm Schäfer
Paderborn University, Germany
,
Program Chairs:
Arie van Deursen
Delft University of Technology, Netherlands
,
Andrea Zisman
Open University, UK

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 ACM 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 August 2017

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Conference

ESEC/FSE'17

Sponsor:

SIGSOFT

ESEC/FSE'17: Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering

September 4 - 8, 2017

Paderborn, Germany

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Overall Acceptance Rate 112 of 543 submissions, 21%

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Ayoughi NNejati SSabetzadeh MSaavedra PEgyed AWimmer MChechik MCombemale B(2024)Enhancing Automata Learning with Statistical Machine Learning: A Network Security Case StudyProceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems10.1145/3640310.3674087(172-182)Online publication date: 22-Sep-2024
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