Contributions related to all aspects of modeling, modeling languages and model-based software and systems engineering are cordially invited to the 25th edition of MODELS, in Montreal, Canada 16-21 October 2022.

MODELS is the premier conference series for model-based software and systems engineering. Since 1998, MODELS has covered all aspects of modeling, from languages and methods, to tools and applications. Attendees of MODELS come from diverse backgrounds, including researchers, academics, engineers, and industrial professionals. MODELS 2022 is a forum for participants to exchange cutting-edge research results and innovative practical experiences around modeling, modeling languages, and model-based software and systems engineering.

As in previous years, MODELS 2022 is offering two tracks for technical papers: the Foundations Track and the Practice & Innovation Track.

This year’s edition will provide an opportunity for the modeling community to further advance the foundations of modeling, and come up with innovative applications of modeling in emerging areas of cyber-physical systems, embedded systems, socio-technical systems, cloud computing, big data, machine learning, security, open source, and sustainability.

For this year’s edition, the conference has the special theme “Modeling for social good” #MDE4SG. Thus, we especially encourage contributions where model-based engineering intersects with research and applications on, not exclusively, socio-technical systems, tools with social impact, integrating human values, data science, artificial intelligence, digital twins, Industry/Society 5.0, and intelligent systems in general.

We invite you to join us at MODELS 2022, Montreal, Canada and to help shape the modeling languages, methods, and technologies of the future!

Topics of Interest (but not restricted to)

MODELS 2022 seeks submissions on diverse topics related to modeling for software and systems engineering, including, but not limited to:

    Foundations of model-based engineering, including definition of syntax and semantics of modeling languages and model transformation languages.
    New paradigms, formalisms, applications, approaches, frameworks, or processes for model-based engineering such as low-code/no-code development, digital twins, etc.
    Definition, usage, and analysis of model-based generative and re-engineering approaches.
    Models@Runtime: model-based monitoring, analysis, and adaptation towards intelligent systems, e.g., with digital shadows or digital twins.
    Development of model-based systems engineering approaches and modeling-in-the-large including interdisciplinary engineering and coordination.
    Applications of AI to model-based engineering problems including e.g., search-based and machine learning approaches.
    Model-based engineering foundations for AI-based systems.
    Human and organizational factors in model-based engineering.
    Tools, meta-tools, and language workbenches for model-based engineering, including model management and scalable model repositories.
    Integration of modeling languages and tools (hybrid multi-modeling approaches).
    Evaluation and comparison of modeling languages, techniques, and tools.
    Quality assurance (analysis, testing, verification) for functional and non-functional properties of models and model transformations.
    Collaborative modeling research to address global and team management issues (e.g., browser-based and cloud-enabled collaboration).
    Evolution of modeling languages and related standards.
    Evidence-based education research for curricular concerns on modeling topics.
    Modeling in software engineering; applications of models to address general software engineering challenges.
    Modeling for specific challenges such as collaboration, scalability, security, interoperability, adaptability, flexibility, maintainability, dependability, reuse, energy efficiency, sustainability, and uncertainty.
    Modeling with, and for, new and emerging systems and paradigms such as security, cyber-physical systems (CPSs), the Internet of Things (IoTs), cloud computing, DevOps, data analytics, data science, machine learning, big data, systems engineering, socio-technical systems, critical infrastructures and services, robotics, mobile applications, conversational agents, open-source software, sustainability and modeling for social good.
    Empirical studies of applying model-based engineering for domains such as smart production, smart cities, smart enterprises, smart mobility, smart society, etc.