This document proposes that modeling should become an independent scientific discipline to better realize its full potential. Currently, modeling is seen primarily as a tool within software engineering, but it is applicable across many domains. An independent modeling discipline could bring together experts from different fields, develop a common body of knowledge and terminology, and help modeling gain more recognition and resources. Some initial steps suggested include making modeling tools more usable and accessible across domains, identifying economic benefits to promote adoption, and facilitating interdisciplinary publishing and education around modeling concepts and applications. The overarching goal is for modeling to serve all domains through a transdisciplinary approach.
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Modeling should be an independent scientific discipline
1. Modeling should be an independent
scientific discipline
@JordiCabot / jordicabot.com / modeling-languages.com
Jordi Cabot, Antonio Vallecillo
Cabot, J., Vallecillo, A. Modeling should be an independent
scientific discipline. Softw Syst Model (2022).
https://doi.org/10.1007/s10270-022-01035-8 (Open access)
3. SOM research lab -
Our mission
Interested in the broad area
of systems and software
engineering, especially
promoting the rigorous use
of software models and
engineering principles in
all software engineering
tasks.
Flickr/clement127
5. Need to reclaim the key role of modeling
and bring it into the limelight
6. • Grady Booch – history of softwre engineering
The entire history of software engineering is that of
the rise in levels of abstraction
- Grady Booch
7. • Everything is a model
• The key role of modeling and abstraction in software engineering
• Their key role also beyond software itself
I think we all agree
8. Low-code application platforms accelerate app
delivery by dramatically reducing the amount of
hand-coding required – Forrester Report
BUT we have a marketing problem…
10. Low-code is trending because
•Much clearer message: Everybody understands
that low-code means “less coding”. MDD is much
more confusing
•Sounds familiar, as the marketing msg is still focus
on the code
•Simpler pipeline, no transformation chains, one-
shot modeling.
•Low-code tools are better <- Usability issues!!!
11. "Given the final model, the complete computerized
information system can be automatically
generated“
"we arrive at a specification from which executable
code can be automatically generated"
Already topics at CAiSE’91
18. • But we can still help with our particular modeling
perspective and expertise
– By building a useful set of abstractions and precise
notations to use them
– “Machinery” to automatically reason on, process and
exchange models build with these abstractions
There is plenty of modeling in other domains
20. To unleash the full potential of modeling we need to break free of
our traditional positioning within software engineering and
cooperate with scientists and engineers from other domains.
The best way to achieve this is for modeling to become an
independent discipline that serves all the rest.
WIN-WIN proposition -> we help others and learn from them
25. Be inclusive
• Understand (and collect) how different
communities model
• Build bridges among different models and
study the benefits of different combinations
of such models
• Develop the proper tooling for this
27. Teaching modeling
• MBEBOK could be a starting point
• Combine a set of core concepts with specializations
for specific domains
– Specialization goes beyond tech concepts, e.g.
effective use of modeling in the domain X based on
the profile of user there
• Different education paths for “modeling users” and
“modeling devs”
28. User driven DSLs
• New DSLs are needed for many domains
where use of modeling is informal
• But these domains are far from our knowledge
• We need to involve the end-users
• Lack of prof modelers -> non-tech people
creating DSLs
29. Usability
• Modeling tools are not that usable, especially for
non experts
• Can we bring modeling to the tools they already
use?
• How to facilitate the modeling process?
– AI to the rescue
– Generation of models from data / docs
30. Economies of modeling
• Methods to compute the ROI of modeling
• Needed to discuss the benefits of adopting
modeling in different scenarios
31. Publishing
• To involve researchers, they must be able to
get something out of their time
• Interdisciplinary publishing is really tough
Though let’s always keep in mind that “AI ISSSSSS Software!!!
For sure, we’re not the only ones modeling
Building an ECAD modeling tool with SysML and EMF as a much cheaper solutions than dedicated ECAD editors
1. Disciplines have a particular object of research, although the object of re-search may be shared with another discipline. Our object of research isto provide languages, operations and tools to create and manipulate ab-stractions that facilitate the comprehension, reasoning and manipulationof complex technical, social, biological and natural systems, and not onlysoftware-based ones. We partner together with other disciplines to reachthese goals.2. Disciplines have a body of accumulated specialist knowledge referring totheir object of research, which is specific to them and not generally sharedwith another discipline. Software modeling has a well-defined body of knowl-edge [10] that characterizes the specific contributions of modeling as aknowledge field.3. Disciplines have theories and concepts that can organize the accumulatedspecialist knowledge effectively. Modeling comprises a good number of theo-ries (some grounded on formal methods, some on more empirical evidence)to compare, merge and organize the growing number of modeling conceptsand techniques being developed.4. Disciplines use specific terminologies or a specific technical language ad-justed to their research object. Over the years, modeling has precisely de-fined a set of core terminology (model, metamodel, DSL, transformation,etc.). New terms are then contextualized in terms of the existing ones (e.g.the positioning of low-code [11, 25]).5. Disciplines have developed specific research methods according to their spe-cific research requirements. Research methods in modeling are mostly de-rived from research methods in software engineering adapted to the speci-ficities of modeling. More work on developing more specific methods thatcan be employed when applying modeling in other fields will be needed.6. Disciplines must have some institutional manifestation in the form of sub-jects taught at universities or colleges. Modeling courses are part of thesyllabus in most computing curricula, and discussions on how to betterteach modeling are an important part of every modeling conference (e.g.see the annual Educators Symposium at the Models conference). Therewas even an attempt to create a full postgraduate course on model-drivenengineering [13]. Even if short-lived, this experience showed that modelingis rich enough to be the focus of a full teaching specialization.
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