Course Details for A.Y. 2019/2020
Name:
Model Driven Engineering / Model Driven Engineering
Basic information
Credits:
: Master Degree in Computer Science 6 CFU (b)
Degree(s):
Master Degree in Computer Science curriculum SDRC Elective
Master Degree in Computer Science curriculum ASSC Elective
Master Degree in Computer Science 1st anno curriculum GSEEM Compulsory
Master Degree in Computer Science curriculum General Elective
Language:
English
Course Objectives
LEARNING OUTCOME
On successful completion of this module, students should be able to:
* Knowledge
Explain the principles and concepts underlying model-driven engineering
Describe concept and approaches for defining the syntax and semantics of domain-specific modelling languages
Define and explain the concepts, syntax and semantics of model transformation languages and mode-to-text tools
Explain the basic concepts and techniques underlying the automated generation of (diagrammatic and textual) modelling editors and environments
* Skills
Use abstraction in the construction of software models and in the definition of domain-specific modelling languages
Apply the EMF frameworks for model-driven engineering, including the definition of meta-models for domain-specific modelling languages
Apply tools for model transformation and model-to-text generation
Apply tools for model construction, model differencing and comparison, model management
* Competence
Assess the applicability and limitations of model-driven engineering and tools for development of software
Judge the practical application of modelling and model management in realistic scenarios
Discuss and document the construction and validation of models and extensions of supporting software tools
Course Content
- Introduction, Metamodeling, General-purpose vs domain-specific modeling, Modeling languages (concrete vs abstract syntax), the metamodeling architecture, the Meta-Object Facility.
- Eclipse EMF
- Model Transformations: MOF Query-View-Transformation, ATL, JTL
- Model management: Model weaving, Model differencing
- Concrete Syntax: EMFText, GMF
- Coupled Evolution: Metamodel/Model co-evolution, Metamodel/Transformation co-evolution, EMF Migrate
Learning Outcomes (Dublin Descriptors)
On successful completion of this course, the student should
- KNOWLEDGE:
Explain the principles and concepts underlying model-driven engineering
Describe concept and approaches for defining the syntax and semantics of domain-specific modelling languages
Define and explain the concepts, syntax and semantics of model transformation languages and mode-to-text tools
Explain the basic concepts and techniques underlying the automated generation of (diagrammatic and textual) modelling editors and environments
APPLICATION:
Use abstraction in the construction of software models and in the definition of domain-specific modelling languages
Apply the EMF frameworks for model-driven engineering, including the definition of meta-models for domain-specific modelling languages
Apply tools for model transformation and model-to-text generation
Apply tools for model construction, model differencing and comparison, model management
EVALUATION:
Assess the applicability and limitations of model-driven engineering and tools for development of software
Judge the practical application of modelling and model management in realistic scenarios
Discuss and document the construction and validation of models and extensions of supporting software tools
Prerequisites and Learning Activities
General admission requirements for the study programme. Background knowledge on the Unified Modelling Language (UML) is an advantage as well as a solid knowledge of the object-oriented paradigm.
Assessment Methods and Criteria
Mandatory assignments:
Taking the oral exam requires that the mandatory assignments have been approved and that the project report has been delivered together with the developed artefacts.
Methods of assessment:
30-minute oral exam about the project work. Both the oral part and the project report part must result in a pass grade in order to pass the course. Moreover, an assessment of the individual assignments will be considered.
Grades are awarded on a scale from 1/30 to 30/30, where 30/30 is the best grade and below 18/30 is a fail. In case, the grade awarded is 30/30 in exceptional cases a “Summa cum Laude” can be awarded as well.
Course page updates
This course page is available (with possible updates) also for the following academic years:
To read the current information on this course, if it is still available, go to the university course catalogue .
Course information last updated on: 11 aprile 2018, 13:47