In this presentation, we summarize the lessons we have learned during the MagicDraw adaptation of VIATRA, Eclipse’s open source framework for scalable reactive model transformations. We have built V4MD, an open source extension for MagicDraw that others can freely reuse and build on, and IncQuery for MagicDraw, a commercial add-on that provides powerful yet user-friendly querying and validation capabilities.

1. EclipseCon France – June 14 2018
Lessons learned from building
Eclipse-based add-ons for
commercial modeling tools
(from a technology perspective)
István Ráth
Ákos Horváth

2. MagicDraw
• A popular modeling tool for UML/SysML, available since 1998
• Over 500.000 downloads in 90 countries
• Standard-compliant and highly customizable platform
• Not just a desktop app, but a complete suite of tools
• Simulation
• Analysis
• Collaboration ! Teamwork Cloud

3. OpenMBEE: an open source ecosystem
• Open modeling platform
• Developed by NASA JPL and others
• Provides
• MMS – collaborative repository with OpenAPI/
Swagger interfaces
• MDK – MagicDraw client built with MD OpenAPI
• DocGen – document generator for SysML models
• View Editor – web-based front-end
• Integrations
(Mathematica, bae, K, DOORS-NG, Matlab)
• A lot of useful and reusable code:
https://github.com/Open-MBEE

4. IncQuery
for MagicDrawTM
and Teamwork CloudTM

5. IncQuery – cloud-based modeling beyond EMF

6. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y

7. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index

8. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index
• MagicDraw &
Teamwork Cloud
• Traditional DBs
• NoSQL & graph DB
• GitHub, …

9. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index
• MagicDraw &
Teamwork Cloud
• Traditional DBs
• NoSQL & graph DB
• GitHub, …
• OpenAPI / Swagger interfaces
• High-performance indexing
• Change updates via callbacks

10. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index
• MagicDraw &
Teamwork Cloud
• Traditional DBs
• NoSQL & graph DB
• GitHub, …
• Clusterized NoSQL
• On-demand
materialization
• Ecore only used for
schema / ontology,
no EMF
instantiation
• OpenAPI / Swagger interfaces
• High-performance indexing
• Change updates via callbacks

11. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index
• MagicDraw &
Teamwork Cloud
• Traditional DBs
• NoSQL & graph DB
• GitHub, …
1000x faster than
conventional DB
technology
• Clusterized NoSQL
• On-demand
materialization
• Ecore only used for
schema / ontology,
no EMF
instantiation
• OpenAPI / Swagger interfaces
• High-performance indexing
• Change updates via callbacks

12. IncQuery – cloud-based modeling beyond EMF
Scalable
Language
tailored to
models
Validation
and
analytics
features
Hybrid
database
technolog
y
Tool / Repository
Persistent
index
VIATRA query & xform
engine
In-memory
index
Containerized
microservices !
Horizontal scaling in
the cloud
• MagicDraw &
Teamwork Cloud
• Traditional DBs
• NoSQL & graph DB
• GitHub, …
1000x faster than
conventional DB
technology
• Clusterized NoSQL
• On-demand
materialization
• Ecore only used for
schema / ontology,
no EMF
instantiation
• OpenAPI / Swagger interfaces
• High-performance indexing
• Change updates via callbacks

13. Scenarios
• Model analysis and validation reporting
(~ “LGTM / FindBugs for models”)
• E.g. check if the signals sent/received over a port correspond to the flow properties
• identify cyclic activity calls
• find deadlock states, i.e. incoming transitions but not outgoing
• Etc.
• Change impact analysis
• If I change an upstream project, how will it affect downstream projects?
• Fast queries ! realizable in pre-commit hooks
• Ad-hoc model queries
• Model comprehension
• Reviews
• Traceability analysis

14. IncQuery for MagicDraw and Teamwork Cloud
Screenshots

15. IncQuery for MagicDraw and Teamwork Cloud
Screenshots

16. IncQuery for MagicDraw and Teamwork Cloud
Screenshots

17. IncQuery is built on open source
http://eclipse.org/viatra
Model query and transformation framework
• Declarative
• Scalable
• Reactive
Easy integration
• Java & other JVM languages
• Enabling libraries for
open & commercial
tools
Major industrial users & partners:

18. IncQuery is built on open source
http://eclipse.org/viatra
Model query and transformation framework
• Declarative
• Scalable
• Reactive
Easy integration
• Java & other JVM languages
• Enabling libraries for
open & commercial
tools
Major industrial users & partners:
What’s new in VIATRA 2.0?
• Simplification
• Fewer third party dependencies
• New language features
• Lots of performance and memory
optimizations
• Java compatibility (Java 8 required &
used on API, Java 9/10 supported)
• Available in Eclipse Photon!

19. MagicDraw and EMF
• Lesson #1 Custom EMF metamodel for UML
• Incompatible with MDT.UML
• Most visible difference: profile support
• Applied profiles and stereotypes can be referenced by name
• „string typing”
• Lesson #2 Custom EMF implementation
• Mostly EMF-compatible, including change notifications! (support
incremental processing out-of-the box)
• Custom memory management (loading-unloading in the background)
• Custom transaction handling

20. MagicDraw and EMF
• Lesson #1 Custom EMF metamodel for UML
• Incompatible with MDT.UML
• Most visible difference: profile support
• Applied profiles and stereotypes can be referenced by name
• „string typing”
• Lesson #2 Custom EMF implementation
• Mostly EMF-compatible, including change notifications! (support
incremental processing out-of-the box)
• Custom memory management (loading-unloading in the background)
• Custom transaction handling
V4MD: VIATRA for MagicDraw
• Open source ”glue code” (EPL v2)
• Demonstrates how to bind EMF-based
tech to MagicDraw
• Deployable as a MD plug-in built with
Gradle
• http://github.com/viatra/v4md

21. MagicDraw vs. OSGi
• MD 18.x+ is based on Eclipse Equinox
• not entirely: the application itself is, but…
• Lesson #3
• MagicDraw plug-ins are not OSGi bundles
• No classpath separation
• MagicDraw API cannot be referenced as OSGi dependencies
• Lesson #4
• Custom plugin.xml format
• Incompatible with PDE

22. Lesson #5: Integrating Xtext into MagicDraw
• Parsing infrastructure is easy to reuse, but...
• As standalone Java application
• Maven dependencies useful
• ... a full-blown editor integration is tricky
• Many dependencies, including SWT and JDT
• Integrating SWT-based UI into Swing is not practical
• Alternatives we considered:
• Future proof: Web-based editor with LSP
• Quick-and-dirty: Separate Eclipse RCP based application

23. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser

24. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”

25. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”
• No dependency issues inside
MagicDraw
• But requires a 200MB RCP app
(per platform)

26. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”
• No dependency issues inside
MagicDraw
• But requires a 200MB RCP app
(per platform)
• Just works
• Custom “protocol” for
communication

27. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”
• No dependency issues inside
MagicDraw
• But requires a 200MB RCP app
(per platform)
• Just works
• Custom “protocol” for
communication
• Can host the language server
• A path forward as technology
matures

28. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”
• No dependency issues inside
MagicDraw
• But requires a 200MB RCP app
(per platform)
• Just works
• Custom “protocol” for
communication
• Can host the language server
• A path forward as technology
matures
• Platform specific issues with
window management

29. Alternatives: LSP vs. RCP
LSP
• Deploy language server within MD
! dependency issues
• Potential collusions with built-in
jars
• No mature LSP client for Swing UI
• Monaco editor has issues with built-
in browser
RCP-based „companion app”
• No dependency issues inside
MagicDraw
• But requires a 200MB RCP app
(per platform)
• Just works
• Custom “protocol” for
communication
• Can host the language server
• A path forward as technology
matures
• Platform specific issues with
window management

30. Simple UML path
expressions
UML Types
Keywords in purple
Check expressions
A "companion app” for MagicDraw:
The VIATRA Query Language Editor
https://www.eclipse.org/viatra/documentation/tutorial.html
https://www.eclipse.org/viatra/documentation/query-language.html
Pattern that lists
SysML Blocks

31. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language

32. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle

33. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting

34. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting
• MagicDraw OpenAPI dependencies
• Download and install MagicDraw instance
• Use as dependency source

35. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting
• MagicDraw OpenAPI dependencies
• Download and install MagicDraw instance
• Use as dependency source
• External dependencies
• Downloaded via standard Gradle mechanisms
• Script can update plugin and installation
descriptor files

36. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting
• MagicDraw OpenAPI dependencies
• Download and install MagicDraw instance
• Use as dependency source
• External dependencies
• Downloaded via standard Gradle mechanisms
• Script can update plugin and installation
descriptor files
• Generated code
• Handled via Gradle plugins

37. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting
• MagicDraw OpenAPI dependencies
• Download and install MagicDraw instance
• Use as dependency source
• External dependencies
• Downloaded via standard Gradle mechanisms
• Script can update plugin and installation
descriptor files
• Generated code
• Handled via Gradle plugins
• Running MagicDraw
• Starts the Platform Runner of MagicDraw
• Parameterized with the Gradle Java Runner

38. Lesson #6: Building MagicDraw plugins
Challenges
• Collect jars from a MagicDraw installation
• Non-standard solution
• Execute new MagicDraw instance with plug-in
• Starting an OSGi container is non-trivial
• Add third-party dependencies
• Maven dependencies
• Plugin descriptors have to include all jar files by
name
• Separate installation descriptor as well in a
different format
• Handling generated code
• VIATRA VQL language
• Xtend language
Solution: Gradle
• Originates from OpenMBEE project
• Gradle-based solution
• Relies on scripting
• MagicDraw OpenAPI dependencies
• Download and install MagicDraw instance
• Use as dependency source
• External dependencies
• Downloaded via standard Gradle mechanisms
• Script can update plugin and installation
descriptor files
• Generated code
• Handled via Gradle plugins
• Running MagicDraw
• Starts the Platform Runner of MagicDraw
• Parameterized with the Gradle Java Runner
MD Plugin Skeleton
• “Hello world” plugin based on the Gradle setup
• Easy to reuse
• https://github.com/IncQueryLabs/MD_plugin_skeleton

39. Some more open source contributions
• MD VIATRA benchmark
• https://github.com/IncQueryLabs/magicdraw-viatra-benchmark
• Scalability benchmark for VIATRA queries over MagicDraw models
• TMT model fork
• https://github.com/IncQueryLabs/TMT-SysML-Model
• Large (300k+) real-world SysML model, very useful to testing tools
• Examples of actual IQ4MD validation rules inspired by NASA JPL
• MDK fork
• https://github.com/IncQueryLabs/mdk
• Example usage of V4MD within MDK, NASA JPL’s toolkit

40. Takeaways

41. Takeaways
• Integrating with proprietary tools is more challenging...
• Compared to a purely open Eclipse ecosystem
• ... But not that hard with the proper tools

42. Takeaways
• Integrating with proprietary tools is more challenging...
• Compared to a purely open Eclipse ecosystem
• ... But not that hard with the proper tools
• No Magic is an open and collaborative partner
• Open ecosystem around MD (on a smaller scale) is worth
exploring
• And contributing to!

43. Takeaways
• Integrating with proprietary tools is more challenging...
• Compared to a purely open Eclipse ecosystem
• ... But not that hard with the proper tools
• No Magic is an open and collaborative partner
• Open ecosystem around MD (on a smaller scale) is worth
exploring
• And contributing to!
• Watch out for VIATRA 2.0 and the IncQuery Server

44. Takeaways
• Integrating with proprietary tools is more challenging...
• Compared to a purely open Eclipse ecosystem
• ... But not that hard with the proper tools
• No Magic is an open and collaborative partner
• Open ecosystem around MD (on a smaller scale) is worth
exploring
• And contributing to!
• Watch out for VIATRA 2.0 and the IncQuery Server
• Get the IncQuery MagicDraw plug-in at https://
incquerylabs.com/incquery
• Complete with tutorial and examples

45. Takeaways
• Integrating with proprietary tools is more challenging...
• Compared to a purely open Eclipse ecosystem
• ... But not that hard with the proper tools
• No Magic is an open and collaborative partner
• Open ecosystem around MD (on a smaller scale) is worth
exploring
• And contributing to!
• Watch out for VIATRA 2.0 and the IncQuery Server
• Get the IncQuery MagicDraw plug-in at https://
incquerylabs.com/incquery
• Complete with tutorial and examples

46. Thank you!
+36 70 633 3973
@IncQueryLabs
iq4md AT incquerylabs.com
http://iq4md.incquerylabs.com
info AT incquerylabs.com