1. Model Driven Architecture (MDA)
An Introduction and
Commonly Research Problems
Ha Lai Duy
Østfold University College
October 19, 2011

2. Outline
 An Introduction
 Commonly Research Problems
 Conclusions

3. Overview about MDA
 Model driven architecture: was launched by
the OMG in 2001.
 Model-centric approach: models are the
main focus of the software process.

4. Traditional Software
Development problems
 Most of the
artifacts during the
first three phases is
just paper and
nothing more.
 Productivity
 Maintenance
 Document
 Portability

5. MDA development process
 The artifacts are
formal models
(which can be
understood by
computers)
 Models are the core
at MDA

6. Model, Language, and System

7. MDA models
 Platform Independent Model (PIM)
 a high level abstraction.
 independent of any implementation
technology.
 Platform Specific Model (PSM)
 tailored to specify system in terms of the
implementation.
 Code
 final artifacts in the development

8. MDA transformation steps

9. Meta-model
 A meta-model is simply a model of a modeling
language.
 It defines the structure, semantics, and
constraints for a family of models.

10. OMG's four-layer architecture

11. Transformation
 Transformation is the automatic process to transform a
set of source models to a set of target model.
 Model to text: Visitor, template.
 Model to model: OMG’s QVT specification in 2008.

12. The Complete MDA Framework
M3
MOF
is is
written written
in in
QVT
is
written
M2 in
UML Transformation ERD
Profiles definition Profiles
defines
M1
Class Transform to Relational
diagram diagram

13. Outline
 An Introduction
 Commonly Research Problems
 Conclusions

14. Commonly Research Problems
 Model
 Transformation
 Metamodelling
 Apply MDA

15. Model research field
 Evaluate the essential of UML in
practice.
 Due to its complexity & power.
 Like 3GLs, it does not fit to model
specific domain problems.

16. Model research field
 Domain Specific Language (DSL)
 Propose the modeling language for
specific domains e.g. ERD, EBNF, XML
Schema, Ontology language,...
 Buid the model-based DSL framework to
take the advantage of MDA features e.g.
code generation, transformation…
 Support to develop a new DSL language
in both notation and textual ways.

17. Model research field
 Model operation
 Support version control system:
 Models comparision.
 Conflict detection and resolution.
 Copy-paste-merge operations.
 Model validation
 Debuging model
 Model query
 Model transaction

18. Transformation research field
 Exploring possibilities and eliciting
requirements.
 Implement the QVT standard.
 Evaluate in practical applications.

19. Transformation research field
 Model interpretation vs. code generation
 Pros:
 It enables faster changes.
 It enables changes at runtime.
 Easier to update and scale.
 Cons:
 Customers could not choose their execution
environment.
 We have the freedom at the model aspect, but we
left the freedom at the generator rules.

20. Metamodelling research field
 The evolution of the meta-models:
 Transformation defination should be
changed to adapt with new meta-model.
 Model is invalid with the new version of
meta-model.
 Co-evolution approaches.

21. Apply MDA in practice
 Software development approaches:
 Agile MDA.
 MDA framework introduces some risks:
 It is too rigid:
 requirement team should understand what is
allowed and what is not.
 The roles is changed in MDA approaches.
 Enviroment for MDA
 Education.
 Culture gap.

22. Outline
 An Introduction
 Commonly Research Problems
 Conclusions

23. Conclusions
 Advantages:
 Gain of productivity.
 High level of abstraction.
 Documentation.
 Maintaining.
 ...
 Disadvantages:
 Rigidity.
 Require the new roles in software development.
 Not fully implementation.
 Does not support version control for collaboration.

24. Conclusions
 Problem statements:
 The rigidtity of MDA:
 When request of change comes:
 Going back and modify the meta-models
 Effect to other artifacts e.g. models
 Hack the code:
 Not well documented  maintaning.
 Manipulating the source models to make it
procudes desire result.
 Models are not truly reflected to the
problem domain.

25. Thank you