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MODELS 2023 : ACM/IEEE 26th International Conference on Model-Driven Engineering Languages and SystemsConference Series : Model Driven Engineering Languages and Systems | |||||||||||||||||
Link: https://conf.researchr.org/home/models-2023 | |||||||||||||||||
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Call For Papers | |||||||||||||||||
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. MODELS participants originate from a wide variety of backgrounds, including researchers, academics, engineers, and industry professionals.
MODELS 2023 is a forum for participants to share the latest research and practical experiences around modeling, modeling languages, and model-based software and systems engineering. Respective contributions advance the fundamentals of modeling and report applications of modeling in areas such as cyber-physical systems, embedded systems, socio-technical systems, cloud computing, big data, machine learning, security, open source, and sustainability. ## Important Dates ## - Abstract Submission: April 07, 2023 - Paper Submission: April 14, 2023 - Author responses: June 5–7, 2023 - Author notification: June 26, 2023 - Camera Ready Due: July 10, 2023 Submission deadlines are hard, i.e., there will be no submission deadline extensions. ## Topics of Interest ## MODELS 2023 solicits submissions on a variety of topics related to modeling for software and systems engineering including, but not limited to: - Fundamentals 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, use, and analysis of model-based generative and re-engineering approaches. - Model-based monitoring, analysis, and adaptation heading towards intelligent systems. - Development of model-based systems engineering approaches and modeling-in-the-large, including interdisciplinary engineering and coordination. - Applications of AI to model-related engineering problems, 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. - Hybrid multi-modeling approaches, i.e., integration of various modeling languages and their tools. - 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 to address team management issues, e.g., browser-based and cloud-enabled collaboration. - Evolution of modeling languages and related standards. - Modeling education, e.g., delivery methods and curriculum design. - Modeling in software engineering, e.g., applications of models to address common 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, novel systems and paradigms in fields such as security, cyber-physical systems (CPSs), the Internet of Things, cloud computing, DevOps, blockchain technology, data analytics, data science, machine learning, Big Data, systems engineering, socio-technical systems, critical infrastructures and services, robotics, mobile applications, conversational agents, and open-source software. - Empirical studies on the application of model-based engineering in areas such as smart manufacturing, smart cities, smart enterprises, smart mobility, smart society, etc. ## Paper Tracks & Submission information ## As in previous years, MODELS 2023 offers two tracks for technical papers: the Foundations Track and the Practice Track. A detailed description of these tracks can be found at the "Foundations Track" and "Practice Track" pages respectively. - Foundation Track: https://conf.researchr.org/track/models-2023/models-2023-technical-track#Foundations-Track - Practice Track: https://conf.researchr.org/track/models-2023/models-2023-technical-track#Practice-Track |
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