short-paper

Learning-based response time analysis in real-time embedded systems: a simulation-based approach

Authors:

Mahshid Helali Moghadam,

Mehrdad Saadatmand,

Björn LisperAuthors Info & Claims

SQUADE '18: Proceedings of the 1st International Workshop on Software Qualities and Their Dependencies

Pages 21 - 24

https://doi.org/10.1145/3194095.3194097

Published: 28 May 2018 Publication History

Abstract

Response time analysis is an essential task to verify the behavior of real-time systems. Several response time analysis methods have been proposed to address this challenge, particularly for real-time systems with different levels of complexity. Static analysis is a popular approach in this context, but its practical applicability is limited due to the high complexity of the industrial real-time systems, as well as many unpredictable runtime events in these systems. In this work-in-progress paper, we propose a simulation-based response time analysis approach using reinforcement learning to find the execution scenarios leading to the worst-case response time. The approach learns how to provide a practical estimation of the worst-case response time through simulating the program without performing static analysis. Our initial study suggests that the proposed approach could be applicable in the simulation environments of the industrial real-time control systems to provide a practical estimation of the execution scenarios leading to the worst-case response time.¹

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Cited By

Radecki ARybicki T(2022)Simulation Oriented Layer of Embedded Software Architecture for Rapid Development of Custom Embedded Systems Virtual Simulators Used in DidacticsApplied Sciences10.3390/app1213632212:13(6322)Online publication date: 21-Jun-2022
https://doi.org/10.3390/app12136322
WU YYAMANE S(2020)Model Checking of Real-Time Properties for Embedded Assembly Program Using Real-Time Temporal Logic RTCTL and Its Application to Real Microcontroller SoftwareIEICE Transactions on Information and Systems10.1587/transinf.2019EDP7172E103.D:4(800-812)Online publication date: 1-Apr-2020
https://doi.org/10.1587/transinf.2019EDP7172
Vicente Nino Rondon CCastro Casadiego SDelgado BIbarra DPosada Haddad M(2020)Real-Time Detection and Clasification System of Biosecurity Elements Using Haar Cascade Classifier with Open Source2020 IX International Congress of Mechatronics Engineering and Automation (CIIMA)10.1109/CIIMA50553.2020.9290295(1-6)Online publication date: 4-Nov-2020
https://doi.org/10.1109/CIIMA50553.2020.9290295
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Learning-based response time analysis in real-time embedded systems: a simulation-based approach

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cover image ACM Conferences

SQUADE '18: Proceedings of the 1st International Workshop on Software Qualities and Their Dependencies

May 2018

53 pages

ISBN:9781450357371

DOI:10.1145/3194095

Program Chairs:
Séverine Sentilles
Mälardalen University, Västerås, Sweden
,
Barry Boehm
USC, Los Angeles, CA
,
Catia Trubiani
Gran Sasso Science Institute (GSSI), L'Aquila, Italy
,
Xavier Franch
Universitat Politecnica Catalunya, Barcelona, Spain
,
Anne Koziolek
Karlsruhe Institute of Technology, Karlsruhe, Germany

Copyright © 2018 ACM.

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Published: 28 May 2018

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ICSE '18: 40th International Conference on Software Engineering

May 28, 2018

Gothenburg, Sweden

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Cited By

Radecki ARybicki T(2022)Simulation Oriented Layer of Embedded Software Architecture for Rapid Development of Custom Embedded Systems Virtual Simulators Used in DidacticsApplied Sciences10.3390/app1213632212:13(6322)Online publication date: 21-Jun-2022
https://doi.org/10.3390/app12136322
WU YYAMANE S(2020)Model Checking of Real-Time Properties for Embedded Assembly Program Using Real-Time Temporal Logic RTCTL and Its Application to Real Microcontroller SoftwareIEICE Transactions on Information and Systems10.1587/transinf.2019EDP7172E103.D:4(800-812)Online publication date: 1-Apr-2020
https://doi.org/10.1587/transinf.2019EDP7172
Vicente Nino Rondon CCastro Casadiego SDelgado BIbarra DPosada Haddad M(2020)Real-Time Detection and Clasification System of Biosecurity Elements Using Haar Cascade Classifier with Open Source2020 IX International Congress of Mechatronics Engineering and Automation (CIIMA)10.1109/CIIMA50553.2020.9290295(1-6)Online publication date: 4-Nov-2020
https://doi.org/10.1109/CIIMA50553.2020.9290295
Chen JYu WZhang YDu C(2019)Design and Implementation of Universal Configurable Digital Emulators2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)10.1109/ITAIC.2019.8785587(943-947)Online publication date: May-2019
https://doi.org/10.1109/ITAIC.2019.8785587
Helali Moghadam MSaadatmand MBorg MBohlin MLisper B(2019)Machine Learning to Guide Performance Testing: An Autonomous Test Framework2019 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW.2019.00046(164-167)Online publication date: Apr-2019
https://doi.org/10.1109/ICSTW.2019.00046

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