The document discusses the concepts of collaborative modeling and metamodeling in software language development, emphasizing the need for multiple experts to ensure quality and correctness in language definitions. It highlights the advantages of parallel efforts in language development, leading to improved efficiency and user acceptance. Collaborative tools and methodologies are presented, such as concurrent repository systems, which enable real-time collaboration and conflict resolution among teams working on models.

1. Juha-Pekka Tolvanen
jpt@metacase.com
Collaborative
modeling and metamodeling

2. Agenda
 Collaborative metamodeling
 Collaborative modeling
 Q&A

3. Experts define languages
& generators
Team models with domain
concepts & generate code
 Integrated
language definition
 No programming
needed
 Language evolution
 Several integrated
languages
 Collaborative
language
engineering
(metamodeling)
 Models update
on any change
 Scalable to
large models
(4 billion)
 Fast
generators
 Interfaces to
various IDEs
(VS, Eclipse)
 Collaborative
modeling
Context for collaboration: MetaEdit+

4. Why collaboration on language
engineering?
 A language definition has several parts:
abstract syntax, constraints, notation & semantic rules
– Single person is often not master of them all
 Language definition need to be consistent,
complete and correct
– If not: see UML standard containing hundreds of errors1 in
abstract syntax and their related constraints
 Single language is not enough, we use several
(integrated) languages
– Multiple persons almost always involved
361 errors in UML 2.0: Bauerdick et al, in Procs of UML 2004, LNCS 3273, Springer, 2004;
320 errors in UML 2.3: Wilke & Demuth, 2010, journal.ub.tu-berlin.de/eceasst/article/download/669/682‎

5. Collaborative metamodeling
(example: TDL by ETSI)
A) Concepts
(Abstract syntax)
B) Constraints
(Static semantics)
C) Notation
(Concrete syntax)
D) Generators
(Semantics)

6. Demonstration:

7. Benefits of collaborative
metamodeling
 Leads to better quality languages
– Languages can be checked early while being defined
– Users may immediately test the language, incl. validation
– When defined in smaller increments the risk of creating the
wrong language constructs is reduced
 Development of languages and generators is faster:
– Parallel effort
– Work shared based on expertise
 Language adoption and acceptance improves since
language users are directly involved

8. Why collaborative modeling?
 Collaboration means working together with the same
model - even at the same time
– Even in the same diagram (not typical, but possible)
– Partly with the same model elements (typical)
 Known and proven technology to enable collaboration:
Repository with concurrency control
– Conflicts detected and handled at the modeling time
• Trace to users
– No need to diff
– No need to merge
– Scales to large models

9. Collaborative modeling
(example: automotive system)
A) Hardware
B) Functions
C) Allocation
D) Behavior
+ 16 other
– Safety
– Errors
– Timing
– ...

10. Demonstration:

11. Benefits of collaborative modeling
 Team can work in the same design space in parallel
– E.g. If feedback is needed from colleagues they all can see
the same model (or model element) and update it
 No time and effort is needed to handle conflicts
 Development is faster as all model information is
available as needed
 Work from multiple views – often based on different
languages – can be integrated at model level
 Trace is available among views and model elements
 Models can be checked and verified early – not based on
one diagram only but on larger model which may be
based on different languages

12. Cases, tutorial, videos, manuals
and evaluation version available
at:
www.metacase.com
Contact: Juha-Pekka Tolvanen (jpt@metacase.com)
Company: info@metacase.com
Thank you!