International Conference on Model Driven Engineering Languages and Systems (MODELS-C)

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.