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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-28285
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dc.contributor.authorBirchler, Christian-
dc.contributor.authorRohrbach, Cyrill-
dc.contributor.authorKim, Hyeongkyun-
dc.contributor.authorGambi, Alessio-
dc.contributor.authorLiu, Tianhai-
dc.contributor.authorHorneber, Jens-
dc.contributor.authorKehrer, Timo-
dc.contributor.authorPanichella, Sebastiano-
dc.date.accessioned2023-07-20T13:54:03Z-
dc.date.available2023-07-20T13:54:03Z-
dc.date.issued2023-
dc.identifier.isbn979-8-3503-2996-4de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/28285-
dc.description.abstractSoftware systems for safety-critical systems like self-driving cars (SDCs) need to be tested rigorously. Especially electronic control units (ECUs) of SDCs should be tested with realistic input data. In this context, a communication protocol called Controller Area Network (CAN) is typically used to transfer sensor data to the SDC control units. A challenge for SDC maintainers and testers is the need to manually define the CAN inputs that realistically represent the state of the SDC in the real world. To address this challenge, we developed TEASER, which is a tool that generates realistic CAN signals for SDCs obtained from sensors from state-of-the-art car simulators. We evaluated TEASER based on its integration capability into a DevOps pipeline of aicas GmbH, a company in the automotive sector. Concretely, we integrated TEASER in a Continous Integration (CI) pipeline configured with Jenkins. The pipeline executes the test cases in simulation environments and sends the sensor data over the CAN bus to a physical CAN device, which is the test subject. Our evaluation shows the ability of TEASER to generate and execute CI test cases that expose simulation-based faults (using regression strategies); the tool produces CAN inputs that realistically represent the state of the SDC in the real world. This result is of critical importance for increasing automation and effectiveness of simulation-based CAN bus regression testing for SDC software.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectAutonomous systemde_CH
dc.subjectRegression testingde_CH
dc.subjectSimulation environmentde_CH
dc.subjectCAN busde_CH
dc.subject.ddc005: Computerprogrammierung, Programme und Datende_CH
dc.titleTEASER : simulation-based CAN bus regression testing for self-driving cars softwarede_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1109/ASE56229.2023.00154de_CH
dc.identifier.doi10.21256/zhaw-28285-
zhaw.conference.details38th IEEE/ACM International Conference on Automated Software Engineering (ASE), Kirchberg, Luxembourg, 11-15 September 2023de_CH
zhaw.funding.euinfo:eu-repo/grantAgreement/EC/H2020/957254//DevOps for Complex Cyber-physical Systems/COSMOSde_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end2061de_CH
zhaw.pages.start2058de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedings2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE)de_CH
zhaw.webfeedSoftware Engineeringde_CH
zhaw.funding.zhawCOSMOS – DevOps for Complex Cyber-physical Systems of Systemsde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.relation.referenceshttps://zenodo.org/record/7964890de_CH
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Birchler, C., Rohrbach, C., Kim, H., Gambi, A., Liu, T., Horneber, J., Kehrer, T., & Panichella, S. (2023). TEASER : simulation-based CAN bus regression testing for self-driving cars software [Conference paper]. 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2058–2061. https://doi.org/10.1109/ASE56229.2023.00154
Birchler, C. et al. (2023) ‘TEASER : simulation-based CAN bus regression testing for self-driving cars software’, in 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, pp. 2058–2061. Available at: https://doi.org/10.1109/ASE56229.2023.00154.
C. Birchler et al., “TEASER : simulation-based CAN bus regression testing for self-driving cars software,” in 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2023, pp. 2058–2061. doi: 10.1109/ASE56229.2023.00154.
BIRCHLER, Christian, Cyrill ROHRBACH, Hyeongkyun KIM, Alessio GAMBI, Tianhai LIU, Jens HORNEBER, Timo KEHRER und Sebastiano PANICHELLA, 2023. TEASER : simulation-based CAN bus regression testing for self-driving cars software. In: 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE). Conference paper. IEEE. 2023. S. 2058–2061. ISBN 979-8-3503-2996-4
Birchler, Christian, Cyrill Rohrbach, Hyeongkyun Kim, Alessio Gambi, Tianhai Liu, Jens Horneber, Timo Kehrer, and Sebastiano Panichella. 2023. “TEASER : Simulation-Based CAN Bus Regression Testing for Self-Driving Cars Software.” Conference paper. In 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2058–61. IEEE. https://doi.org/10.1109/ASE56229.2023.00154.
Birchler, Christian, et al. “TEASER : Simulation-Based CAN Bus Regression Testing for Self-Driving Cars Software.” 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE), IEEE, 2023, pp. 2058–61, https://doi.org/10.1109/ASE56229.2023.00154.


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