Papers
1
Total Citations
13
H-Index
1
About
Ludovic Deval is a leading researcher at the intersection of Model-Driven Engineering (MDE) and robotics, with a focus on bridging the gap between high-level design and practical implementation. His most-cited work, "Bootstrapping MDE Development from ROS Manual Code - Part 2: Model Generation" (2019, 13 citations), tackles a critical challenge in robotics software development: while MDE promises to let domain experts work with expressive models and automate code generation for diverse hardware, most real-world robotics code remains manually written. Deval’s key contribution is a bootstrapping approach that automatically generates models from existing ROS (Robot Operating System) manual code, effectively lowering the barrier to adopting MDE in robotics. This work demonstrates how to reverse-engineer models from legacy systems, enabling incremental migration to model-driven practices without requiring a complete rewrite. By showing that MDE can be practically introduced into existing ROS-based projects, Deval has provided a pathway for more systematic, reusable, and maintainable robotics software development. His research is particularly valuable for students and engineers seeking to modernize robotic systems, offering a pragmatic bridge between theory and the messy reality of industrial codebases.
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