MDE Intelligence

4th Workshop on Artificial Intelligence and Model-driven Engineering
Co-located with MODELS. October 23-28, 2022. Montreal, Canada.


Theme & Goals

Artificial Intelligence (AI) has become part of everyone's life. It is used by companies to exploit the information they collect to improve the products and/or services they offer and, wanted or unwanted, it is present in almost every device around us. Lately, AI is also impacting all aspects of the system and software development lifecycle, from their upfront specification to their design, testing, deployment and maintenance, with the main goal of helping engineers produce systems and software faster and with better quality while being able to handle ever more complex systems and software.

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.

This workshop provides a forum to discuss, study and explore the opportunities and challenges raised by the integration of AI and MDE.

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 software, in fact), we also believe that such AI-powered MDE approach will also benefit the design of AI artifacts themselves and specially to face the challenge of designing "trustable" AI software.

Last but not least, although AI is the most popular branch of computer science to create and simulate intelligence, we also believe that any kind of technique that provides human cognitive capabilities and helps creating "intelligent" software are also in the scope of this workshop. An example would be the knowledge representation techniques and ontologies that can be useful on its own or support other kinds of AI techniques.

Call for Papers

Model-driven engineering (MDE) and artificial intelligence (AI) are two separate fields in computer science, which can clearly benefit from cross-pollination and collaboration. There are at least two ways in which such integration—which we call MDE Intelligence—can manifest:

  • Artificial Intelligence for MDE. MDE can benefit from integrating AI concepts and ideas to increase its power: flexibility, user experience, quality, etc. For example, using model transformations through search-based approaches, or by increasing the ability to abstract from partially formed, manual sketches into fully-shaped and formally specified meta-models and editors.
  • MDE for Artificial Intelligence. AI is software, and as such, it can benefit from integrating concepts and ideas from MDE that have been proven to improve software development. For example, using domain-specific languages allows domain experts to directly express and manipulate their problems while providing an auditable conversion pipeline. Together this can improve trust in and safety of AI technologies. Similarly, MDE technologies can contribute to the goal of fair and explainable AI.


Topics of interest for the workshop include, but are not limited to:

  • AI for MDE

    • Application of (meta-heuristic) search to modelling problems;
    • Machine learning of models, meta-models, concrete syntax, model transformations, etc.;
    • AI planning applied to modelling, meta-modelling, and model management;
    • Modeling assistants such as bots, conversational agents and virtual assistants/recommenders supporting diverse modeling tasks;
    • Model inferencers and automatic model generators from datasets;
    • Self-adapting code generators;
    • Semantic reasoning;
    • AI-supported model-based digital twins;
    • AI-based user interface adaptation for modeling tools;
    • AI with human-in-the-loop for modeling;
    • Semantic reasoning, knowledge graphs, and domain-specific ontologies;
    • Probabilistic models;
    • AI techniques for data, process and model mining and categorisation;
    • Natural language processing applied to modeling;
    • Data quality and privacy issues in AI for MDE.
  • MDE for AI

    • Domain-specific modelling approaches for AI planning, machine learning, agent-based modelling, etc.;
    • Model-driven processes for AI system development;
    • MDE techniques for explainable and fair AI;
    • Using models for knowledge representation;
    • Code-generation for AI libraries and platforms;
    • Architectural languages for AI-enhanced systems;
    • MDE for federated learning;
    • Model-based testing of AI components.
  • General

    • Tools for combining AI and MDE;
    • Experience reports, case studies, and empirical studies;
    • Challenges to be addressed by combining AI and MDE techniques.


Papers will follow the same formatting guidelines as the main tracks of the conference (please check them here). We ask for two type of contributions:
  • 1) Research papers: 8 pages,
  • 2) Vision papers, experience papers or demos: 5 pages.
Submissions must be uploaded through EasyChair in the following link .

All submissions will follow a single-blind review process where each paper will be reviewed by at least 3 members of the program committee. They will value the relevance and interest for discussions that will take place at the workshop. Accepted papers will be published in the ACM MODELS Companion Proceedings.

Papers submitted to MDE Intelligence 2022 must not be under review or submitted for review elsewhere whilst under consideration for MDE intelligence 2022. Contravention of this concurrent submission policy (as stated explicity by the ACM on will be deemed as a serious breach of scientific ethics, and appropriate action will be taken in all such cases.


  • Paper submission: July 20, 2022
  • Notification: August 19, 2022
  • Camera-ready: September 9, 2022
  • Workshop: October 23-28, 2022


This year's MODELS conference will feature a Best Theme Paper Award spanning across all tracks. The special theme of this year’s conference is "Modeling for social good" #MDE4SG. MDE Intelligence is part of this initiative and will have the opportunity to nominate one paper that will be selected by the program committee. We encourage submissions that are relevant to this special theme.


The 4th edition of the MDE Intelligence workshop will be co-located with MODELS 2022 and aims to discuss current work and challenges at the intersection of MDE and AI.

During the workshop, there will be a session of lightning talks around the topics that fall under the scope of the workshop.

We believe that lightning talks are a great opportunity for presenters to promote their work, to receive timely and helpful feedback and to find new collaborations. At the same, these talks will be beneficial for the workshop participants as they may broaden their knowledge and they will be able to actively participate and engage in the discussion around the presented topics.

If you are interested in presenting a lightning talk, please follow the instructions below.

Presenters will have 1-2 minutes to communicate their ideas and they can choose to use up to one slide.

We encourage the submission of proposals around the following topics:

  • Already published works that are relevant for the workshop audience;
  • Discussion of personal visions and ideas;
  • Provocative statements about the past, present or future of the field;
  • Unsolved challenges in academia, industry, open source communities, etc.

      Proposals must be submitted using the submission form. The deadline for submitting proposals is October 15, 2022.


Program schedule (all times relate to local time in Montréal)

Monday, October 24th
8:30 - 10:00 Session I: MDE for AI
  • Welcome
  • Dynamic Data Management for Continuous Retraining
    by Nils Baumann, Evgeny Kusmenko, Jonas Ritz, Bernhard Rumpe and Moritz Benedikt Weber
  • MDE for Machine Learning-Enabled Software Systems: A Case Study and Comparison of MontiAnna & ML-Quadrat
    by Jörg Christian Kirchhof, Evgeny Kusmenko, Jonas Ritz, Bernhard Rumpe, Armin Moin, Atta Badii, Stephan Günnemann and Moharram Challenger
  • Feature-Oriented Modularization of Deep Learning APIs
    by Yechuan Shi, Jin Guo and Jörg Kienzle
10:00-10:30 Coffee break
10:30 - 12:00 Session II: Keynote by Prof. Houari Sahraoui
12:00-13:30 Lunch break
13:30 - 15:00 Session III: AI for MDE
  • Augmenting Model-Based Systems Engineering with Knowledge
    by Luis Palacios, Florian Noyrit and Chokri Mraidha
  • Towards a Configurable Crossover Operator for Model-Driven Optimization
    by Stefan John, Jens Kosiol and Gabriele Taentzer
  • Towards Automatically Extracting UML Class Diagrams from Natural Language Specifications
    by Song Yang and Houari Sahraoui
  • Industrial Generic Requirements for Supporting AI-Enhanced Model-Driven Engineering
    by Johan Bergelin and Per Erik Strandberg
15:00-15:30 Coffee break
15:30 - 17:00 Session IV: Lightning Talks and Discussion
  • Lightning Talks (tbd)
  • Discussion
  • Wrap-Up


  • Biography:

    Houari Sahraoui is a professor at the software engineering lab GEODES of the department of computer science and operations research, Université de Montréal. He holds a Ph.D. in Computer Science from Pierre & Marie Curie University - LIP6 (1995), with a specialization in Artificial Intelligence (AI). His research interests include automated software engineering (SE) and the application of AI techniques to SE. He has published around 200 papers in conferences, workshops, books, and journals. He has served as a program committee member in several IEEE and ACM conferences, as a member of the editorial boards of four journals, and as an organization member of many conferences and workshops. He was the general chair and program chair of many conferences such as IEEE/ACM International Conference on Automated Software Engineering (ASE), ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS), and IEEE Working Conference on Software Visualization (VISSOFT). He and his students have authored several award-winning papers.

Houari Sahraoui




  • Shaukat Ali (Simula Research Laboratory, Norway)
  • Syed Juned Ali (TU Wien Informatics, Austria)
  • Jessie Carbonnel (Université de Montréal, Canada)
  • Juri Di Rocco (University of L'Aquila, Italy)
  • Antonio Garmendia (JKU Linz, Austria)
  • Jose Antonio Hernandez-Lopez (Universidad de Murcia, Spain)
  • Ludovico Iovino (Gran Sasso Science Institute, Italy)
  • Kamal Karlapalem (IIIT Hyderabad, India)
  • Shekoufeh Kolahdouz Rahimi (University of Isfahan, Iran)
  • Bentley Oakes (Université de Montréal, Canada)
  • Aurora Ramírez (University of Córdoba, Spain)
  • Iris Reinhartz-Berger (University of Haifa, Israel)
  • Benoit Ries (University of Luxembourg, Luxembourg)
  • Adrian Rutle (Bergen University College, Norway)
  • Rijul Saini (McGill University, Canada)
  • Daniel Strüber (Radboud University Nijmegen, Netherlands)
  • Gabriele Taentzer (Philipps-Universität Marburg, Germany)
  • Marina Tropmann-Frick (Hamburg University of Applied Sciences, Germany)



If you have questions, contact us by email at: