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MODELS 2021 : ACM/IEEE 24th International Conference on Model Driven Engineering Languages and Systems

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Conference Series : Model Driven Engineering Languages and Systems
 
Link: https://conf.researchr.org/home/models-2021
 
When Oct 10, 2021 - Oct 15, 2021
Where Fukuoka, Japan
Abstract Registration Due Apr 30, 2021
Submission Deadline May 7, 2021
Notification Due Jul 12, 2021
Final Version Due Jul 31, 2021
Categories    software engineering   formal method   embedded system   languages
 

Call For Papers

Call for papers

FOUNDATIONS TRACK

We invite authors to submit high quality contributions describing significant, original, and unpublished results in the following categories:

1. Technical Papers

Technical papers should describe innovative research in modeling or model-driven engineering activities. Papers in this submission category should describe a novel contribution to the field and should carefully support claims of novelty with citations to the relevant literature.

Evaluation Criteria: Technical papers are evaluated on the basis of originality, soundness, relevance, importance of contribution, strength of validation, quality of presentation and appropriate comparison to related work. Where a submission builds upon previous work of the author(s), the novelty of the new contribution must be described clearly with respect to the previous work. Technical papers need to discuss clearly how the results were validated (e.g., formal proofs, controlled experiments, rigorous case studies, or simulations). Authors are strongly encouraged to make the artifacts used for the evaluation publicly accessible, e.g., through a Github repository or an alternative that is likely to remain available. There will be an artifact evaluation process, as discussed below.

2. New Ideas and Vision Papers
We solicit short papers that present new ideas and visions. Such papers may describe new, non-conventional model-driven engineering research positions or approaches that depart from standard practice. They can describe well-defined research ideas that are at an early stage of investigation. They could also provide new evidence that common wisdom should be challenged, present new unifying theories about existing modeling research that provides novel insight or that can lead to the development of new technologies or approaches, or apply modeling technology to radically new application areas.

Evaluation Criteria: New ideas and vision papers will be assessed primarily on their level of originality and potential for impact on the field in terms of promoting innovative thinking. Hence, inadequacies in the state-of-the-art and the pertinence, correctness, and impact of the idea/vision must be described clearly, even though the new idea need not be fully worked out, and a fully detailed roadmap need not be presented.

PRACTICE AND INNOVATION TRACK

The goal of this track is to fill the gap between foundational research in model-based engineering (MBE) and industrial needs. We invite authors from academia and/or industry to submit original contributions reporting on the development of innovative MBE solutions in industries, public sector, or open-source settings, as well as innovative application of MBE in such contexts. Examples include:

- Scalable and cost-effective methodologies and tools
- Industrial case studies with valuable lessons learned
- Experience reports providing novel insights

Each paper should provide clear take-away value by describing the context of a problem of practical importance, and the application of MBE that leads to a solution.

Evaluation Criteria: A paper in the P&I Track will be evaluated mainly from its practical take-away and the potential impact of the findings. More specifically, The paper should discuss why the solution to the problem is innovative (e.g., in terms of advancing the state-of-practice), effective, and/or efficient, and what likely practical impact it has or will have; The paper should provide a concise explanation of approaches, techniques, methodologies and tools employed; The paper should explain best practices that emerged, tools developed, and/or software processes involved.
Studies reporting on negative findings must provide a thorough discussion of the potential causes of failure, and ideally a perspective on how to solve them.Call for papers

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