21st Workshop on Model Driven Engineering, Verification and Validation (MoDeVVa 2024)
MoDeVVa will take place on Sunday, 22 September 2024, in Linz, Austria (co-located with MODELS 2024).
Keynote Speaker: Prof. Joachim Denil (University of Antwerp - FlandersMake, Belgium)
From Validation to Continual Validation: Evolving Digital Twin Systems
Digital twins, digital representations of systems, have become common in solving problems and optimising various systems, e.g., factory scheduling. Simulation models play a crucial role in the decision-making processes of a digital twin. Validation, in simulation model engineering, is checking that a model accurately represents the actual system under design. This is distinct from verification, which is concerned with the proper implementation of the model.
Simulation validation is done during the system's design phase. However, as systems become operational, change emerges to keep the systems useful. These changes occur for a variety of reasons, e.g., wear and tear, component replacement in the actual system, changes in the operational domain of the system. As the system evolves in its context, so should the twin models. In this keynote, we look at the problem of digital twin evolution and its repercussions on the twin model.
Bio: Prof. Dr. Joachim Denil is an associate professor at the University of Antwerp, Faculty of Applied Engineering in Electronics and ICT. His research interests are enabling methods, techniques and tools to design, verify and evolve Cyber-Physical Systems. Specifically, he is interested in the performance modelling and simulation, model-based systems engineering, and verification and validation of models and systems. He serves as an associate editor of the Transaction of the SCS: Simulation. His email address is [email protected] .
Models are purposeful abstractions of systems and their environments. They can be used to understand, simulate, and validate complex systems at different abstraction levels. Thus, the use of models is of increasing importance for industrial applications. Model-Driven Engineering (MDE) is a development methodology that is based on models, metamodels, and model transformations. The shift from code-centric software development to model-centric software development in MDE opens up promising opportunities for the verification and validation (V&V) of software. On the other hand, the growing complexity of models and model transformations requires efficient V&V techniques in the context of MDE.
The workshop on Model Driven Engineering, Verification and Validation (MoDeVVa) offers a forum for researchers and practitioners who are working on V&V and MDE. The main goals of the workshop are to identify, investigate, and discuss mutual impacts of MDE and V&V.
For the 2024 edition of the MoDeVVa workshop we would like to encourage papers addressing the use of AI techniques such as machine learning, to help address the challenges of model-based V&V, Process Engineering and Quality Assurance, while continuing to welcome work in all areas in the intersection between MDE and V&V.
Scope
Modelling is a powerful technique for handling the complexity of software and hardware artifacts, and their respective environments. Model Driven Engineering (MDE) provides efficient tools for building and working with models, from the requirements specification of a system to code-generation, testing, configuration and deployment. Through the systematic use of digital models, which can be processed automatically by programs, MDE offers the opportunity to verify and validate every step in the life cycle of a system. Thus, the first motivation for MoDeVVa is the integration of verification and validation (V&V) techniques into MDE.
While V&V can be seen as an enabler in MDE, it presents a set of challenges of its own. These challenges includes issues of usability and integration with MDE processes as well as the technical difficulties of performing V&V tasks.
One way of addressing these challenges is by taking ad-vantage of MDE itself in V&V tasks, for example by means of domain-specific modelling languages (DSMLs) to capture requirements, system properties, specifications and system de-sign, and leveraging all MDE has to offer such as abstraction, refinement, model-transformations and other techniques, to help perform V&V tasks. Thus, the second motivation for MoDeVVa is the integration of MDE techniques into V&V.
Another way of addressing the challenges posed by V&V in MDE is to leverage novel techniques from AI. The advent of practical machine learning techniques and frameworks opens the way for novel approaches to model-based V&V, which are poised to improve the usability and range of V&V. Thus, the third motivation for MoDeVVa is the integration of novel approaches to the challenges presented by V&V and MDE.
Both MDE and V&V intend to help solve “real-world”problems. Real-world problems and systems are complex.Both MDE and V&V propose approaches to tackle such complexity. Thus, the fourth motivation for MoDeVVa is the applicability of MDE and V&V to complex, real-world problems.
Objectives
The overarching objective of the MoDeVVa workshop is to bring together researchers and practitioners in the domain of V&V and MBSE/MDE so that the key issues in the integration of MDE and V&V can be identified and solved.
More concretely, MoDeVVa's main objectives are to address the following questions:
How can V&V tools and techniques be integrated into MDE in such a way that expertise in V&V is not required in order to obtain the benefits that V&V offers?
How can MDE be leveraged to facilitate V&V tasks?
How can novel approaches such as Machine Learning be leveraged to facilitate V&V in MDE?
How can the combination of MDE and V&V help to address the development of complex real-world systems?
How can MDE be leveraged to facilitate industry to acquire certification for their systems or qualification of their development processes and tools?
How to deploy V&V in ``lightweight'' modeling environments that do not use explicit metamodeling or heavy modeling infrastructures?
How MDE and V&V help in increasing confidence in modern systems involving more and more AI components?
Special issue
We are pleased to announce that the best papers from MoDEVVa and the SAM Conference will be invited to submit extended versions jointly published in a special issue of Innovations in Systems and Software Engineering: a NASA Journal (ISSE) published by Springer Nature !!
Topics of Interest
We welcome contributions in all areas at the intersection of MBSE/MDE and V&V. Papers addressing the following topics are particularly welcome:
V&V in MBSE/MDE
Theoretical frameworks and approaches for integration of V&V in MBSE/MDE.
Formalisms and theories for the specification and verification of models.
Formal approaches to models, modeling languages, including DSMLs and MDE in general.
Modeling relations for checking model conformance and/or refinement.
The application and combination of different V&V techniques (e.g., classical testing, static analysis, model checking, deductive approaches, runtime verification) to MBSE/MDE artifacts.
V&V in “lightweight” modeling environments that do not use explicit metamodeling or heavy modeling infrastructures
MDE in V&V, Certification and Quality Assurance
Use of MDE abstractions (models, meta-models, model transformations) in V&V tasks.
Use of model-evolution approaches to enable incremental V&V.
Industrial case studies for application of MDE for quality assurance.
Model-based process engineering to acquire certification.
Process engineering to support V&V activities.
Tools, usability, and applications
Integration between modeling tools, IDEs and V&V back-ends.
Innovative approaches for model-based V&V of “real-world” systems.
Tools and techniques that help reduce the semantic gap between models and back-end formalisms used in V&V tasks.
Case studies and applications of V&V in MBSE/MDE.
AI-related topics for V&V activities
Use of Machine Learning (ML) to assist model-based V&V activities (e.g., testing selection, generation and prioritization)
AI-enabled model inspection
AI-enabled frameworks/processes for model-based testing
Current practices/case-studies/experience reports on applying ML-assisted model-based V&V.
Use of MDE and V&V in systems that involve AI components
Organizers
Saad Bin Abid (CARIAD SE/Alten, Germany)
Jens Kosiol (Philipps-Universit ̈at Marburg, Germany and Universit ̈at Kassel, Germany)
Rakshit Mittal (University of Antwerp - Flanders Make, Belgium)
Iulian Ober (ISAE-SUPAERO, Université de Toulouse, France)
Ernesto Posse (Lumenix/Zeligsoft, Canada)
Contact: [email protected]