Model-Driven Engineering Training for Industry Professionals (Online)

Session 1: What is Model and Modeling? 

Objective: Understand the fundamental concepts of models and modeling in the context of model-driven engineering.

Topics:

• Definition of models: abstractions representing systems, components, or processes 

• Purpose of modeling: simplifying complexity, improving communication, enabling automation

• Types of models: structural, behavioral, functional 

• Role of models in model-driven engineering: requirements analysis, design, and implementation 

• Benefits and challenges of modeling in industry projects

Session 2: MDSE Principles 

Objective: Explore the principles of Model-Driven Software Engineering (MDSE).

Topics:

• Core MDSE concepts: models as primary artifacts, automation, and abstraction 

• Model-driven vs. code-centric development: benefits and trade-offs

• MDSE principles: separation of concerns, model transformation, and code generation 

• Role of MDSE in improving productivity and quality in software development 

• Industry applications of MDSE (e.g., automotive, aerospace)

Session 3: Introduction to Modeling Languages

Objective: Understand various modeling languages and their design principles.

Topics:

• General-purpose modeling languages: UML, SysML, BPMN 

• Domain-specific modeling languages (DSMLs): examples (e.g., AADL for aerospace, Simulink for control systems) 

• Design principles for DSMLs: expressiveness, usability, extensibility 

• Case studies of DSMLs in industry (e.g., healthcare, telecommunications)

Session 4: Language Engineering (Meta-Modeling) 

Objective: Learn the process of language engineering through meta-modeling for domain-specific problems.

Topics:

• Meta-modeling concepts: meta-models, meta-meta-models, MOF (Meta-Object Facility) 

• Language engineering process: defining domain concepts, relationships, and constraints 

Session 5: Meta-Modeling Technologies 

Objective: Discuss the key requirements, expectations, and challenges in using meta-modeling technologies for DSML development.

Topics:

• Meta-modeling requirements: Language Definition, Modeling Editor (editing modes, syntactic and semantic services), Language Validation, Language Testing, Language Composability

• Practitioners’ expectations and common challenges based on survey results

• Tool usage trends: Which technologies are most used and why?

• What can be done with meta-modeling tools in practice?  

• Practitioner expectations for editor usability, versioning, integration, and hybrid visualization

• Comparison of major technologies: EMF (Sirius, Xtext), MetaEdit+, GME, JetBrains MPS

• Criteria for selecting tools based on domain needs and practical feedback

Session 6: Developing DSMLs with MetaEdit+ ()

Objective: Learn to develop DSMLs, including meta-models, concrete syntax, and modeling editors, using MetaEdit+.

Topics:

• MetaEdit+ overview: architecture, features, and workflow 

• Defining meta-models and concrete syntax (notations, symbols, visual representations) in MetaEdit+ 

• Building modeling editors: integrating meta-models, syntax, and user interactions 

Session 7: Developing Model Transformers with MetaEdit+ 

Objective: Understand and implement model transformations for DSMLs using MetaEdit+.

Topics:

• Model transformation concepts: model-to-model, model-to-code 

• MetaEdit+ transformation capabilities: code generation, model validation, model simulation, and transformation rules 

• Designing transformations for specific outputs (e.g., Java, C++, XML) 

• Debugging and testing transformations in MetaEdit+

Session 8: Case Study and Practical Workshop 

Objective: Apply meta-modeling, syntax definition, editor development, and transformation through a practical case study using MetaEdit+.

Topics:

• Developing a DSML for a real-time traffic management system: traffic flow modeling, signal control, IoT integration 

• Defining meta-models, concrete syntax, modeling editors, and transformations in MetaEdit+ 

• Best practices for integrating all components into a cohesive DSML

Session 9: Model-Driven Digital Twins and System Integration

Objective: Explore the application of model-driven approaches to digital twins and system integration.

Topics:

• Concept of digital twins: virtual representations of physical systems 

• Role of DSMLs in modeling digital twins for real-time monitoring and simulation 

• Model-driven system integration: connecting DSMLs with IoT, cloud, and enterprise systems 

• Challenges and best practices for integrating digital twins with existing systems
  
  

Delivery Method

• Format: Fully online, interactive lectures, hands-on exercises, and group discussions conducted via a video conferencing platform (e.g., Zoom, Microsoft Teams). 

• Tools: 

  • Meta-modeling and editor development: MetaEdit+ (MetaCase), with fallback to Draw.io or OpenModelica for simulation if needed.

  • Collaboration: Miro, Google Docs, or VS Code Live Share for group activities.

• Materials: Digital slide deck, downloadable handouts (MetaEdit+ guides, meta-modeling templates, DSML examples, case study documents), and access to recorded sessions (if permitted). 

• Technical Requirements: Stable internet, webcam, microphone, and access to cloud-based tools. MetaEdit+ license or trial access required (pre-session setup guide provided).
  
  

Learning Outcomes

By the end of the 10-Hour Online Model-Driven Engineering Training, participants will be able to:

1. Understand Models and Modeling Concepts: Define models as abstractions of systems, components, or processes, and explain their importance in model-driven engineering (MDE) for simplifying complexity, enhancing communication, and enabling automation in domains like automotive, aerospace, and IoT.

2. MDSE Principles: Comprehend Model-Driven Software Engineering (MDSE) principles, including separation of concerns, model transformation, and code generation, and recognize their benefits for productivity and system quality compared to code-centric approaches.

3. Understand Meta-Models and Meta-Modeling: Explain meta-models, meta-meta-models (e.g., MOF), and the meta-modeling process, understanding their role in defining domain-specific concepts, relationships, and constraints for language engineering.

4. Understand Modeling Languages: Analyze general-purpose modeling languages (e.g., UML, SysML) and domain-specific modeling languages (DSMLs), and evaluate their expressiveness, usability, and extensibility for domains like healthcare or telecommunications.

5. Understand Meta-Modeling Tools: Compare meta-modeling technologies (e.g., EMF, MetaEdit+, GME, JetBrains MPS) based on language definition, editor usability, and integration capabilities, and assess their suitability for specific project needs.

6. Develop a DSL with MetaEdit+: Use MetaEdit+ to create a simple domain-specific language (DSL) in a case study, defining meta-models, concrete syntax (notations, symbols), and building interactive modeling editors for practical application.

7. Apply Model Transformations in MetaEdit+: Implement model-to-model and model-to-code transformations in MetaEdit+ for a case study, generating outputs like Java, C++, or XML, and validating models for accuracy using code generators.

8. Conduct a Practical DSL Case Study: Build and analyze a DSL for a simple real-time system in MetaEdit+, integrating meta-modeling, editor development, and transformations, and experimenting with traffic flow or IoT components.

9. Understand Digital Twins in MDE: Comprehend the role of DSMLs in modeling digital twins as virtual representations of physical systems, and their application in real-time monitoring and simulation for domains like industrial automation or IoT.

10. Experiment with Model Simulation and Analysis: Use MetaEdit+ to perform model simulation and analysis in a case study, validating DSL behavior and assessing system requirements through practical experimentation.
    
    

For more information about this course, please contact: mert.ozkaya@yeditepe.edu.tr

To enroll in a course, please complete the form by clicking HERE.