Meta-Modelling Kindness (MODELS 2024 - Technical Track) - MODELS 2024

Sun 22 - Fri 27 September 2024 Linz, Austria

Who

Faeq Alrimawi, Bashar Nuseibeh

Track

MODELS 2024 Technical Track

Time Zone

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When

Wed 25 Sep 2024 14:00 - 14:18 at HS 7 - Applications (1) Chair(s): Nelly Bencomo

Faeq Alrimawi

Lero - the Science Foundation Ireland Research Centre for Software

Ireland

Bashar Nuseibeh

The Open University, UK

United Kingdom

Time Zone

The program is currently displayed in (GMT+02:00) Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna.

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Time Band

By setting a time band, the program will dim events that are outside this time window. This is useful for (virtual) conferences with a continuous program (with repeated sessions).
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Session Program

Wed 25 Sep
Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

	14:00 - 15:45	Applications (1)Tools and Demonstrations / Technical Track at HS 7 Chair(s): Nelly Bencomo Durham University

	14:00 18m Talk		Meta-Modelling KindnessFT Technical Track Faeq Alrimawi Lero - the Science Foundation Ireland Research Centre for Software, Bashar Nuseibeh The Open University, UK
	14:21 18m Talk		Mutation Testing of Java Bytecode: A Model-Driven ApproachPT Technical Track Christoph Bockisch , Deniz Eren , Sascha Lehmann , Daniel Neufeld , Gabriele Taentzer Philipps-Universität Marburg
	14:42 18m Talk		IMP-Logics: a metamodel for analysis and transformations of Datalog programs Tools and Demonstrations José Francisco Crespo Universitat Politècnica de Catalunya, Martí Juanola I Ametller Universitat Politècnica de Catalunya, Xavier Oriol Universitat Politècnica de Catalunya, Martí Recalde Universitat Politècnica de Catalunya, Ernest Teniente Universitat Politècnica de Catalunya, Spain
	15:03 18m Talk		Concretize: A Model-Driven Tool for Scenario-Based Autonomous Vehicle Testing Tools and Demonstrations Jerry Hou-Liu McGill University, Zhekai Jiang EPFL / McGill University, Aren Babikian McGill University Link to publication DOI
	15:24 12m Talk		Towards Automated Test Scenario Generation for Assuring COLREGs Compliance of Autonomous Surface VehiclesFTVISION Technical Track Ulf Kargén , Daniel Varro Linköping University / McGill University