Inhalt

[ 921SOENMDEK13 ] KV Model-driven Engineering

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
3 ECTS M1 - Master's programme 1. year Computer Science Alexander Egyed 2 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2025W
Learning Outcomes
Competences
Students can effectively use models to drive engineering decisions and processes. They have a comprehensive understanding of how models play a crucial role in various engineering disciplines and can appreciate the integration of software engineering models with engineering domains. They have acquired practical skills for applying model-driven techniques using Eclipse EMF-based tools. They are able to explore the principles of domain-specific modeling languages and can leverage model-driven engineering to enhance the software engineering process.
Skills Knowledge
  • Utilize Eclipse EMF-based tools (K2): Students will demonstrate their ability to use tools like xtext, ATL, and Sirius for model-driven engineering tasks.
  • Apply meta modeling concepts (K3): Students will apply knowledge of meta models to create and modify modeling frameworks.
  • Execute model transformations (K4): Students will analyze and execute transformations between different models to meet engineering requirements.
  • Develop domain-specific modeling languages (DSLs) (K5): Students will evaluate and develop DSLs to address specific domain needs.
  • Implement code generation and evolution (K6): Students will create and implement processes for generating and evolving code based on models.
  • Integrate model-driven engineering in practice (K6): Students will create practical solutions that incorporate model-driven principles for real-world software engineering problems.
  • Basic MDE Concepts: Understanding fundamental concepts such as model-driven engineering, meta modeling, and model transformation.
  • Meta Modeling: Knowledge of how to design and work with meta models to define modeling languages.
  • Model Transformation: Familiarity with techniques and tools for transforming models into other representations or formats.
  • Domain-Specific Modeling Languages (DSLs): Insights into the creation and application of DSLs tailored to specific engineering domains.
  • Code Generation/Evolution: Knowledge of methods for generating and evolving code from models to ensure alignment with evolving requirements.
Criteria for evaluation Homework
Language English
Study material Comprehensive slides are provided
Changing subject? No
Corresponding lecture INMAWVOMENG: VO Model Engineering (3 ECTS)
On-site course
Maximum number of participants -
Assignment procedure Direct assignment