Ulrik Eklund published a summary of the keynote speech from Jon Whittle at the SPLC 2010 conference. In his talk, he presented some findings on experiences from using model-based development in industry from the EA-MDE project. The project is interested in understanding the factors that lead to success or failure with model-driven engineering (MDE) to help design the next generation of MDE tools. This question is not new, two years ago, Sven Efftinge, Peter Friese and Jan Köhnlein published an article "MDD best practices and Johan Den Haan, CTO of Mendix, published an article on the how an MDD initiative could fail. Adopting an MDE approach can be quite daunting. Then, Johan concluded his article by:A esta invitación final de Jean-Jacques a discutir le siguieron muchas e interesantes respuestas. Siguen algunas de ellas:
It’s not my goal to discourage you from starting with model-driven software development. I just wanted to show you the complexity of it and wanted to share some thoughts hopefully pointing you at directions helping you to overcome the complexity of MDE.Two weeks ago he also published an article on his blog detailing the lessons he learned while building a Model Driven Software Factory and he reiterated the same skepticism:
I see Model Driven Software Development as an important part of the future of software development. However, I also see a lot of people struggle with actually using Model-Driven techniques and applying them in their daily business. It isn't trivial to build a successful Model-Driven Software factory (MDSF).
The question is actually quite popular. Last week, Marco Bramballi and Stefano Butti also published a presentation on the same topic while applying BPM and MDD to a Large Scale banking scenario with BPMN, WebML and WebRation.
In his talk, Jon provided some key success factors of a successful MDE approach, as he identified as part of his research:
In their articles, Swen, Peter and Jan also warned:
- Keep the domains (modelled, I assume) tight and narrow.
- Target well known domains.
- Put MDD on the critical path (he means that pilot projects never get sufficient attention and resources).
- MDD works best form the ground up.
- Be careful of gains that are offset elsewhere.
- Don't obsess about code generation.
- Not everyone can think abstractly.
- Most projects fail at scale-up
- Match tolls and processes to the way people think, not the other way around
Our most important recommendation for the reader is: be pragmatic. DSLs and code generators can, when used appropriately, be an immensely useful tool. But the focus should always be the problem to be solved. In many cases, it makes sense to describe certain, but not all, aspects using DSLs.Even though MDE is still evolving quite rapidly, Jon reports that 83% of the EA-MDE survey respondents "consider MDE a good thing".
After over a decade of Model Driven Architecture, Development and Engineering and which itself followed some rich Model Driven Development environments like NeXTStep that emerged in the early late 80s, models are everywhere, yet, in such a small quantity that our industry seems to still be looking for the path that will make Model-Driven approaches mainstream. Are we really in the position of defining "lessons learned" or "best practices" with so few successes reported? What is hampering us? Is it the focus and precisions of the model? Is it lack of tools? standards? Is is the level of abstraction that make it difficult for most people to create a viable software factory? What's your take on it?
Rui Curado, autor de su propia herramienta, destaca algo que comparto:
Existing model-driven approaches were conceived by "top-notch" developers/mathematicians. This lead to the assumption that those who would use such approaches are "top-notch" developers too. And this is precisely what is happening: Current MDD practitioners belong to the "top 1%".Sobre el enfoque orientado a objetos de las actuales herramientas orientadas a MDD, dice Dean Wampler:
Most of the world's developer population (myself included) are what I call the "average developer mortal": developers who are good at their job without actually being "geniuses". People who do things the right way, but pragmatically. We are the "everyday programmer". MDD approaches and tools fail to address us
[...] all the MDD approaches that I know of are based on objects. Unfortunately, objects have proven to be poor at defining reusable component standards. That's a controversial statement, but to prove it, ask yourself why the world's most successful "component" standards, like TCP/IP, HTTP, busses in digital electronics, etc. are not object oriented, while OO-based component standards, like CORBA, proved to be too complex to survive the test of time and to achieve ubiquitous, permanent adoption. (Still not convinced? "Design Rules, Vol. 1: The Power of Modularity" discusses the characteristics of successful modularity standards. Very few OO APIs meet those criteria.)Dice Steven Kelly, sobre las condiciones para elaborar un modelo satisfactorio:
The key issues are:
1) use a language that is highly targeted, efficient and precise at describing the systems you want to build (and thus useless for most other systems)
2) generate production quality code that you don't need to look at or touch
3) use a toolset that makes creating the language, generators and models efficient, scalable and maintainable.
[...] Failing to reach (or even aim for) those 3 targets is what consigns most MDD attempts to mediocrity or failure. Using a tool or language because it's a "standard" or already in use is hardly likely to result in major productivity increases compared to normal. As Einstein said, insanity is doing the same things as before and expecting different results.Steven, respondiendo a una pregunta de Dubray, dice, respecto a su afirmación de generación completa de código:
100% code generation is definitely the goal, and the norm is to achieve it. Here, 100% means 100% of the code that is specific to this model. There is of course hand-written code below the generated code: what we call the domain framework, i.e. code specifically written to complement this modeling language and generators, and which doesn't change per model.Una vez más, un punto cuestionado es el uso de UML, que es confrontado con DSL (Domain Specific Languages). Por supuesto, Steven Kelly, uno de los gestores de Metaedit, es quien especialmente pone el acento en DSM (Domain Specific Modelling). Dice Kelly:
In some cases a particular model may need an addition to the domain framework; in others models may contain snippets of code or refer to per-model functions that are hand-coded separately.
If by "custom models" you mean "custom modeling languages", then yes, at least that has been my experience. I'm not sure it's "inherently" true, but I think there are good reasons for it. Have you ever seen a tricky or laborious problem can be turned into something an order of magnitude faster and easier by applying the correct language? If so, you probably understand what I'm talking about. Obviously, in general development those situations were rare, because the right language didn't yet exist. DSM lets you create that "right language" for your needs.
As Dean Wampler said, "Give me a language and APIs that let me express what I need to do very succinctly!" That of course is the whole idea of DSM, and why it is so different from (say) UML-based MDA. It's just a shame that working "code generation" often gets tarred with the same brush as approaches that have failed.
Of course, we're all constrained by what we have experienced personally, e.g. Dean saying that all MDD he has seen has been based on object-oriented languages (I guess referring to UML?). It's just a fact that by nature humans trust personal experience far more than even statistically significant research.
Dean said "Nothing beats a Turing-complete, textual programming language for expressivity and productivity." That may be true if you have to pick one language to use for every single task for your whole life. But for any given problem space, it's simply not true. Expressivity is the ability to say everything you want, precisely and concisely - which is as good a definition of a Domain-Specific Modeling language as you're likely to get. The consistent measured increase in productivity by a factor of 5-10 with DSM is a proven fact. And when you've actually seen DSM in practice, as opposed to code generation with UML or IDE wizards, it's obvious why it is so much faster throughout.
Mi impresión: Sigue siendo un hecho que MDD es un concepto en construcción y evolución. Tras años de acento en UML como herramienta básica de elaboración de modelos, la no obtención de resultados robustos ha llevado a un punto en que se exploran otras alternativas. Probablemente, esa robustez llegará, y las variantes actuales serán sólo una parte de las herramientas que sobrevivan. Lo que no sucederá, es que el desarrollo vuelva atrás a herramientas que no impliquen generación de código y un grado alto de abstracción.