There is no doubt that MDE has been a means to tame until now part of this complexity. However, its adoption by industry still relies on their capacity to manage the underlying methodological changes including among other things the adoption of new tools. To go one step further, we believe there is a clear need for AI-empowered MDE, which will push the limits of "classic" MDE and provide the right techniques to develop the next generation of highly complex model-based system and software systems engineers will have to design tomorrow... We would like to address topics such as how to choose, evaluate and adapt AI techniques to Model-Driven Engineering as a way to improve current system and software modeling and generation processes in order to increase the benefits and reduce the costs of adopting MDE. We believe that AI artifacts will empower the MDE tools and boost hence the advantages, and then adoption, of MDE at industry level... At the same time, AI is software (and complex..
Also known as: Method Grid
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Interest Score
1
HIT Score
0.71
Domain
mde-intelligence.github.io

Actual
mde-intelligence.github.io

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185.199.108.153, 185.199.109.153, 185.199.110.153, 185.199.111.153

Status
OK

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Other
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