Keep reading to see how we managed to combine modeling and continuous delivery and how this combination is beneficial for both continuous integration / deployment and model-driven tools
Cognification is the application of knowledge to boost the performance and impact of a process. We believe cognification could be a revolution in the way software is built.
Model-driven engineering is the perfect complement to domain-driven design by providing DDD with the tools to realize its promise
Summary of my invited talk at the RuleML+RR conference where I discussed why rules are not first-class citizens in software engineering and why this has to change to keep up with the demands of big data and open data.
A new approach to bring the benefits of version control to models, implemented in the MetaEdit+ tool
Convention over configuration aims to simplify development by decreasing the number of decisions developers need to make. MDE has a similar goal. Let's see how to combine them.
Ten thngs to keep in mind when mixing modeling and big data. Modeling is as important as ever when dealing with big data but it must be adapted
The rise of low-code platforms, the latest reincarnation of model-driven engineering and code-generation tools
A collection of UML opinions by the people that was there when the language was created. Check what they think 20 years after the creation of the language
Some ideas to make round-trip engineering between UML and programming languages easier. Will this be the solution of this major challenge in MDE?
Are you a programmer or a developer? What's the difference (from our point of view)?
Looking at Cyber-Physical Systems from a modeling / software engineering perspective. What are the challenges and the opportunities?
Learn why this SME uses Python/Django as preferred programming environment, how they use UML, the development method they follow and much more!
See what languages you could use to describe your next Web (RESTful) API and why this is so important to facilitate the consumption of your APIs
Lessons learnt after observing how scientits develop their climate models (and how we could help them) by Steve Easterbrook
Why isn't modelling common place?. In this post I identify five main reasons we need to address to make modeling mainstream.
The problems are growing and MDx should be able to address the challenges more effectively than mainstream approaches. MDx must be the hottest ticket on the software planet then, right? Right?
What makes an open source software successful (in terms of commits, contributors,...)? I have no idea but this post explains one thing that will NOT work
Reevaluating the 'models vs programs' discussion plus the benefits of developing with executable models
Today is the day that we address the R in Scrall. And this week’s blog is