Adoption of MDE technologies (and techniques) could be dis- cussed within the context of existing technology acceptance models (TAMs). For instance, Davis’ basic TAM model [4] emphasizes (perceived) usefulness and ease of use. While these factors are clearly relevant, we aim at a more refined view by paying special attention to how MDE, at this stage, is driven by research and university teaching. That is, we describe the challenge of improving chances of MDE adoption (i.e., improved ‘adoptability’) in terms of maturing three legs of an ‘adoption chair’: i) reproducibility of research re- sults; ii) reusability of essential technologies; iii) teachability of the underlying techniques.

1. Dipartimento di Ingegneria e Scienze
Università degli Studi dell’Aquila
dell’Informazione e Matematica
MDE Adoption:
a three legged chair
Alfonso Pierantonio
joint work with
Juri Di Rocco, Davide Di Ruscio,
Ludovico Iovino, and Ralf Lämmel

2. Technology Acceptance Models
Adoption of MDE could be discussed
within the context of existing
technology acceptance models

3. «Perceived usefulness and
perceived ease of use are
fundamental determinants of user
acceptance.»
F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information
Technology.,” MIS Quarterly, 1989.

4. Alfonso Pierantonio – GRAND 2017, Marburg
4
Perceived Usefulness
The degree to which a person believes that using a
particular system would enhance her performance
Abstraction + Automation

5. Alfonso Pierantonio – GRAND 2017, Marburg
5
Perceived Usefulness
The degree to which a person believes that using a
particular system would enhance her performance
Abstraction + Automation
There is a general consensus about abstraction
(even among "model-skeptics”): it turns any
programmer into a good programmer (or modeler)

6. Alfonso Pierantonio – GRAND 2017, Marburg
6
Perceived Usefulness
The degree to which a person believes that using a
particular system would enhance her performance
Abstraction + Automation
While automation is widely used in certain
technical spaces (eg. XML), it is generally confined
within niche communities (eg. metaprogramming)

7. Alfonso Pierantonio – GRAND 2017, Marburg
7
Aesthetic of complexity
Most computer scientists have a sense of beauty towards
complexity («the more complex, the cooler»), which may
compromise ease of use
– Besides accidental complexity [1] there is a also a form of
unneeded complexity, which goes beyond the essential
complexity
It can be explained in different ways
– Lack of vision
– Easy of use not considered relevant
– Individuals might have a negative, bullistic attitude to
demonstrate forms of superiority over peers or teammate
[1] Brooks, Fred P. (1987). "No Silver Bullet — Essence and Accidents of Software
Engineering". IEEE Computer. 20 (4): 10–19.

8. Adoption of MDE
It is jeopardized by complexity of tooling
environment, plethora of languages,
limited maturity level (often academic
only),
lack of documentation, etc

9. reproducIbility
reusabilityteachability
adoptability

10. Alfonso Pierantonio – GRAND 2017, Marburg
10
Reproducibility of research result
The ability of an entire analysis of an experiment to
be duplicated, either by the same researcher or by
someone else
– there is no grand scheme of achieving reproducibility in the
MDE field
– several SE venues, have started to run artifact evaluation
process, which arguably relates to reproducibility
– reproducibility enhance reusability in an academic context
and thus also teaching

11. Alfonso Pierantonio – GRAND 2017, Marburg
11
Reusability of essential technologies
The artifact evaluation of SLE’16 was based on the
principle that “a good artifact is: consistent with the
paper, as complete as possible, well-documented,
easy to (re)use”
– reusability is severely limited because of, for example,
reliance on specific IDE versions and constrained plugin
combinations
– compare this with reusability of web technologies, as an
extreme example, consider JSFiddle

13. Alfonso Pierantonio – GRAND 2017, Marburg
13
Teachability of the underlying techniques
Are we able to teach MDE techniques with justifiable effort?
There is not a general consensus on what a course on
modeling and MDE should necessarily contain
– a taxonomy of modeling concepts can be useful
We struggle to teach MDE techniques, courses may
– be too abstract by refraining from using technologies
– leverage an MDE technology expert and overwhelm students on
technologies
Techniques may be buried in Interactive tools, evolving
languages, and research prototypes and involve non-trivial
setups not always automated or reasonably explainable
R. F. Paige, F. A. C. Polack, D. S. Kolovos, L. M. Rose, N. D. Matragkas, and J. R. Williams, “Bad Modelling
Teaching Practices.,” EduSymp@MoDELS, 2014

14. Alfonso Pierantonio – GRAND 2017, Marburg
14
Maturing the legs
Apparently, model repositories may help
– keeping them alive and solicit contributions from user
communities is a hard task
Our proposal is to
– reverse engineering to semi-automatically collect MDE
projects in a centralized repository,
– enrich the projects by architectural and semantic
information, tell underlying authors about findings, and
permit refinements

15. Alfonso Pierantonio – GRAND 2017, Marburg
15
Maturing the legs
It is important to shift the focus from ‘collection of
models’ to ‘collection of (reproducible, reusable,
teachable) projects’
– Going beyond what current repositories can do
– Combination of cloud-/web-based approach and
megamodeling to enhance reusability and teachability in
terms of build management, regression testing,
deployment, executability, and visualization
– Get rid of superfluous complexity
Ultimately, the resulting repository may become a
truly useful chrestomathy