Model-driven Prompt Engineering
We propose a DSL for prompt engineering to define platform-independent prompts that can later be adapted to provide good quality outputs in any target AI system
Managing design-time uncertainty in OCL expressions
We propose an extension to the OCL notation to be able to model constraints even when we do not have enough domain information to be completely precise about the rule we are modeling
Diverse scenario exploration in model finders using graph kernels and clustering
Clustering of model instances by using graph kernels. Make sure you test your models with the most diverse set of examples!
From informal to formal modeling
We propose an iterative modeling approach where designers can dynamically customize the level of formality required in each iteration in a visual and intuitive way
Incremental verification of software models
If we want software verification techniques to be more adopted in the industry, we need to move to incremental verification approaches, where we reuse previous analysis to avoid reevaluating the whole model every time it is modified.
The low-code handbook
Modeling: all you need to know
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