Co-located with MODELS. October 23-28, 2022. Montreal, Canada.
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.
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:
Topics of interest for the workshop include, but are not limited to:
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:
Proposals must be submitted using the submission form. The deadline for submitting proposals is October 15, 2022.
|8:30 - 10:00||Session I: MDE for AI|
|10:30 - 12:00||Session II: Keynote by Prof. Houari Sahraoui|
|13:30 - 15:00||Session III: AI for MDE|
|15:30 - 17:00||Session IV: Lightning Talks and Discussion|
Over the past decades, the software engineering research community has made significant advances in automating software development and maintenance tasks. This was achieved thanks to the accumulation of knowledge produced by many clusters of researchers working on general-purpose artifacts such as automatic generation of test data, refactoring, program repair or feature location. However, automating domain-specific tasks did not benefit from the same critical masses of researchers. This is particularly the case of manipulating models described with domain-specific languages. In this presentation, we discuss the use of genetic programming to transform data or examples of a specific domain into knowledge to automate modeling tasks of that domain. We also briefly report on recent advances in using deep-learning models to support modeling activities.
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.
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