Modeling is more popular than ever, even if sometimes hidden behind other names (e.g. low-code). But of course, we can always do better. In this talk, I'll describe the main technical/social challenges modeling is facing and the key trends that could solve them. We'll even throw some AI, Machine Learning and bots in the mix to show how modeling can be also useful there and even more, benefit from them, to move towards a smarter modeling future.

1. Future Trends on Modeling
18th of June, 2020
Jordi Cabot
ICREA Research Professor at UOC
Jordi.cabot@icrea.cat
@softmodeling / modeling-languages.com
#SiriusCon

2. Why Modeling?

3. I model,
therefore I am
- René Descartes

4. • Grady Booch – history of softwre engineering
The entire history of software engineering is that of
the rise in levels of abstraction
- Grady Booch

6. To model, or not to model, this is the WRONG
question
- Shakespeare

7. What/when/how many
models ?
Depends on: Size, Team,
Domain,….
Real question (difficult!)
Modeling ROI: Cost
of modeling vs Bº of
modeling <- Cost
depends on tools!

8. Modeling what?

9. This is a
model
(that you all
understand)

10. Engineering
Systems
SW
Everything is a model
SW is probably the
worst market for
selling modeling

11. SysMLe Profile: a SysML Profile for ECAD

12. Modeling in…

13. Moving towards modeling is the natural evolution
in any domain (e.g. Machine Learning)

14. Why not more modeling?

15. BUT he is saying
this since 1985

16. History of ML
History of Modeling
Langs – J.P. Tolvanen

17. We have a marketing problem

18. Modeling is not sexy (in some communities, e.g. devs)
• Low-code is modeling with another name that just sells more
• Modeling has bad press (mostly due to salesmen selling UML as a
silver bullet)
• Exception: Reverse Engineering (OpenAPItoUML, JSONDiscoverer,…)
People believe that modeling …
• Is not agile
• Is just for documentation (and a posteriori)
• Is just nice pictures

19. VCs believe in “modeling” (when marketing it well!)

20. We have a usability problem

21. Have you ever found a user that loves her
modeling tool?
• Too many clicks
• Too many options
• Eclipse/EMF was a great environment
Not a Good first impression
• Lack of documentation
• Installation/Configuration issues
• Generated code not optimized

22. We have an infrastructure problem

23. Modeling is also:
• Collaboration
• Security
• Confidentiality
Adapted to where the users are/want
• GitHub (textual modeling)
• Online (web-based editors)
• Flexible (inconsitent, lightweight MDE)

24. And there’s more

25. Bucchiarone, Cabot,
Paige, Pierantonio:
Grand challenges in
model-driven
engineering: an
analysis of the state of
the research. Software
and Systems Modeling
19(1): 5-13 (2020)

26. What about better modeling?

27. New Interfaces for Modeling

28. Textual models are models
• Lower barrier to entry
• Easier to integrate in CI pipelines
• One DSL -> multiple notations
– Killer combination: textual notation to write the
model, graphical one to visualize & read it

29. E.g. Modeling of chatbots (xatkit.com)
Daniel, Cabot, Deruelle, Derras:
Xatkit: A Multimodal Low-Code
Chatbot Development Framework.
IEEE Access 8: 15332-15346 (2020)

30. Moving to the cloud
• All Programming IDEs are moving to the cloud
• Modeling IDEs should follow suit
• Multiple JS libraries can be used in the front-end
• In the back-end:
EMF-REST

31. Modeling outside modeling tools

32. Modeling with VoiceBots / Chatbots
Pérez-Soler, Daniel, Cabot, Guerra, de Lara:
Towards Automating the Synthesis of Chatbots for Conversational Model Query. EMMSAD@CAiSE 2020: 257-265

33. Openness comes with new challenges
• Intellectual Property Protection
– Robust Hashing for models
• Accountability
– Blockchain infrastructure for models
• Security
– Access-control for models
• Scalability
– NoSQL backends like NeoEMF

34. AI-based modeling

35. Smarter tools
makes us more
productive
https://modelia.eu/

36. Mendix Assist

37. OutSystems.ai

38. Model autocompletion from textual data
• Previous approaches are based on historical
models. Only useful if you have many models
• What every project has is lots of documents
• We’re developing an NLP-based model
autocompletion

39. AI for manipulationg models: the MT
example
Original model
… CODE
Software code1 refinementst n refinementth
Model-to-model
Transformation
Model-to-text
Transformation
CODE
CODE
• Requires learning a new language (the MT Language)
• Time consuming
• Error prone

40. Let’s try to learn the MTs automatically
Input
Output
Training Transforming
ML Input OutputML
Machine Learning
Artificial Neural Networks
Deep Networks
Recurrent networks
LSTM
BPMN
Petri nets
BPMN Petri Net

41. Tree-to-Tree Encoder-decoder arquitecture
InputModel
(preprocessed)
InputTree
EmbeddingLayer
Encoder
LSTM
network
OutputTree
ExtractionLayer
OutputModel
(non-postprocessed)
Decoder
LSTM
network
AttentionLayer
InputModel
OutputModel
Preprocessing
Postprocessing
Burgueño, Cabot, Gérard: An LSTM-Based Neural Network Architecture for Model
Transformations. MoDELS 2019: 294-299
We are developed a similar approach for model-to-code transformations. Useful to
mimick the company’s programming style.

42. Personal modeling

43. We live in a modeling multi-verse
We need to
develop domain-
specific modeling
environments to
better serve the
needs of users in
different domains

44. Models are not a static, fixed
and complete artifact. Rather a
partial, dynamic, personal and
temporal view of the domain
How tools and languages should adapt to better
serve this view?

45. Customization
• It should be easy to adapt tools to your
specific needs
– Even better: morphing modeling tools that
automatically adapt based on what you do.
• Also the notations
– Personal notations sharing a common abstract
syntax

46. Views and viewpoints
Brunelière, García Perez, Wimmer, Cabot:
EMF Views: A View Mechanism for Integrating Heterogeneous Models. ER 2015: 317-325
EMF
Views

47. Extensible/Composable DSLs
• No one size fits all solution. Let’s not reinvent
UML
• Set of modeling libraries/packages to import into
a small core DSL
– Uncertainty modeling
– Temporal modeling
– Spatial modeling
• Somehow going back to the idea of (EMF) Profiles

48. We’re getting there…

49. More modeling questions?

50. Let’s work
together
jordi.cabot@
icrea.cat
@softmodeling
modeling-
languages.com

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