In line with the research theme of this year’s RE conference, the workshop topics include efforts to expand the frontiers of RE through model-based techniques. However, submissions are also welcome in all workshop topics such as:

    Modeling languages and metamodels for requirements engineering approaches
    Modeling languages and metamodels for supporting separation of concerns in requirements models
    Modeling languages and metamodels for non-functional requirements
    Modeling languages and metamodels for requirements engineering for specific domains, such as cyber-physical systems and IoT, Big Data, AI applications, and Industry 4.0
    Through life model-driven assurance of the non-functional requirements of cyber-physical systems
    AI-driven generation of models for the assurance of the non-functional requirements of cyber-physical systems
    Model-driven regulatory compliance of cyber-physical systems
    Model-driven representation, detection, and mitigation of assurance deficits in assurance case models
    Synchronicity and consistency of different requirements models and views
    Requirements models for machine learning and deep learning solutions
    Requirements models at runtime
    Requirements models for human values, ethics, fairness, and equality
    Requirements models for sustainability and GreenIT
    Automatic analysis and simulation of requirements models
    Traceability and correctness of model transformations involving requirements models
    AI approaches for model transformations involving requirements models
    Flexible and collaborative modeling in requirements engineering
    Empirical studies on model-driven requirements engineering
    Automatic generation of tools for RE using MDD
    Research methods from other disciplines, such as sociology, for eliciting requirements models
    Requirements engineering approaches for low-code/no-code software development

Moreover, industry papers covering topics such as the following are highly welcome:

    Industry problems and practices
    Success stories about adopting model-driven requirements engineering in industry
    Industrial empirical studies