How to Make Robust and Scalable Modeling Workbenches with Sirius
You have already built a modeling workbench thanks to Sirius and you are going to deploy it on a large scale?
So you may need a deeper understanding on how Sirius works and learn about how to make your tool more robust and more scalable.
During this talk, we will give some insights about internal Sirius mechanisms, for example how Sirius computes the elements which are displayed in your modeler.
Then we will explain some design and configuration choices that can impact the performance of your tool:
- how to write efficient expressions?
- how to avoid useless evaluations?
But deploying a tool also means that you will have to face maintenance and evolution challenges. This talk will also be the opportunity for me to share some best practices that will make your modeling tool stronger and more flexible.
This talk is targeted to people who have already played a little with Sirius and created their own modelers with it (even very simple ones), and want to go to the next step.