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MODELS 2024
ACM/IEEE 27th International Conference on
Model Driven Engineering Languages and Systems
September 22-27, 2024
Linz, Austria
https://conf.researchr.org/home/models-2024
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MODELS is the premier conference series for model-based software and systems
engineering. Since 1998, MODELS has covered all aspects of modeling, from
languages and methods, to tools and applications. Attendees of MODELS come from
diverse backgrounds, including researchers, academics, engineers, and
industrial professionals. MODELS 2024 is a forum for participants to exchange
cutting-edge research results and innovative practical experiences around
modeling, modeling languages, and model-based software and systems engineering.
This year's edition will provide an opportunity for the modeling community to
further advance the foundations of modeling, and come up with innovative
applications of modeling in emerging areas of cyber-physical systems, embedded
systems, socio-technical systems, cloud computing, big data, machine learning,
security, open source, and sustainability.
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**** Important Dates ****
Abstract Submission: March 21, 2024
Paper Submission: March 28, 2024
Author responses: May 27-29, 2024
Author notification: June 17, 2024
Camera Ready Due: July 31, 2024
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**** Topics of Interest (but not restricted to) ****
MODELS 2024 solicits submissions on a variety of topics related to modeling for
software and systems engineering including, but not limited to:
* Fundamentals of model-based engineering, including the definition of syntax
and semantics of modeling languages and model transformation languages.
* New paradigms, formalisms, applications, approaches, frameworks, or processes
for model-based engineering such as low-code/no-code development, digital
twins, etc.
* Definition, use, and analysis of model-based generative and re-engineering
approaches.
* Model-based monitoring, analysis, and adaptation heading towards intelligent
systems.
* Development of model-based systems engineering approaches and
modeling-in-the-large, including interdisciplinary engineering and coordination.
* Applications of AI to model-related engineering problems, e.g., approaches
based on search, machine learning, large language models (AI for modeling)
* Model-based engineering foundations for AI-based systems (modeling for AI)
* Human and organizational factors in model-based engineering.
* Tools, meta-tools, and language workbenches for model-based engineering,
including model management and scalable model repositories.
* Hybrid multi-modeling approaches, i.e., integration of various modeling
languages and their tools.
* Evaluation and comparison of modeling languages, techniques, and tools.
* Quality assurance (analysis, testing, verification, fidelity assessment) for
functional and non-functional properties of models and model transformations.
* Collaborative modeling to address team management issues, e.g., browser-based
and cloud-enabled collaboration.
* Evolution of modeling languages and related standards.
* Modeling education, e.g., delivery methods and curriculum design.
* Modeling in software engineering, e.g., applications of models to address
common software engineering challenges.
* Modeling for specific challenges such as collaboration, scalability,
security, interoperability, adaptability, flexibility, maintainability,
dependability, reuse, energy efficiency, sustainability, and uncertainty.
* Modeling with, and for, novel systems and paradigms in fields such as
security, cyber-physical systems (CPSs), the Internet of Things, cloud
computing, DevOps, blockchain technology, data analytics, data science, machine
learning, Big Data, systems engineering, socio-technical systems, critical
infrastructures and services, robotics, mobile applications, conversational
agents, and open-source software.
* Empirical studies on the application of model-based engineering in areas such
as smart manufacturing, smart cities, smart enterprises, smart mobility, smart
society, etc.
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As in previous years, MODELS 2024 offers two tracks for technical papers:
the Foundations Track and the Practice Track. A detailed description of these
tracks can be found at:
https://conf.researchr.org/track/models-2024/models-2024-technical-track
NEW THIS YEAR: Foundations Track welcomes both short and long New Ideas and
Vision Papers
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**** FOUNDATIONS TRACK ****
We invite authors to submit high-quality papers describing significant,
original, and unpublished results in the following categories:
1. Technical Papers
Technical papers should report on innovative research in modeling or
model-driven engineering activities. They should describe a novel contribution
to the field and carefully demonstrate the novelty by referencing relevant
related literature.
Evaluation Criteria:
Technical papers will be evaluated based on originality, soundness, relevance,
significance, strength of validation, quality of presentation, and quality of
related work discussions. Submissions must clearly and explicitly describe what
is novel about their contribution in comparison to prior work. Results must be
validated by formal proofs, rigorous demonstrations (e.g., rigorous case
studies or simulations), or empirical evaluations (e.g., controlled experiments
or surveys). Authors are strongly encouraged to make the artifacts used for the
evaluation publicly available, e.g., via a GitHub repository or an alternative
that is expected to provide long-term availability. A respective artifact
evaluation process is described below.
2. New Ideas and Vision Papers
New ideas and vision papers describe original, non-conventional research
positions in modeling or model-driven engineering and/or approaches that
deviate from standard practice. They describe well-defined revolutionary
research ideas that are in the early stage of the investigation. They might
provide evidence that common wisdom should be challenged, present unifying
theories about existing modeling research that can provide new insights or lead
to the development of new technologies or approaches, or apply modeling
technology to unprecedented application areas.
Evaluation Criteria:
New ideas and vision papers are either short or long papers. Both will be
assessed primarily on their degree of originality and potential for advancing
innovation in the field. As such, new ideas and vision papers are expected to
follow a specific format, and provide a compelling and revolutionary argument.
Note that this category is not intended for foundation or practice papers
without sufficient evaluation. Such papers will not be accepted. Submissions
must clearly describe shortcomings of the state-of-the-art and the relevance,
correctness, and impact of the idea/vision. New ideas and vision papers need
not be fully worked out and a detailed roadmap need not be provided. The use of
worked-out examples to support new ideas is strongly encouraged. Long papers
must also supply some degree of validation. However, we accept less rigorous
methods of validation such as compelling arguments, exploratory
implementations, and substantial examples.
Authors are also strongly encouraged to make any artifacts publicly available,
e.g., via a GitHub repository or an alternative that is expected to provide
long-term availability. A respective artifact evaluation process is described
below.
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**** PRACTICE TRACK ****
The goal of the Practice Track is to bridge the gap between foundational
research in Model-Based Engineering (MBE) and needs in practice. We invite
authors to submit original contributions that report on the application of MBE
solutions in the industry, the public sector, or open-source environments.
Examples include:
* Demonstrations of scalable and cost-effective methodologies and tools.
* Case studies or field reports offering valuable insights.
* Comparisons of competing approaches in real-world scenarios.
* Submissions need to communicate the context of the application and the
practical importance of the findings. Unlike the application itself, any
reported lessons learned or insights gained must be original.
Evaluation Criteria:
A paper in the Practice Track will be evaluated primarily on the potential
impact of its findings. Specifically:
* The paper must describe the context of the MBE application and what problem
it solves/addresses.
* The paper should include a concise explanation of the approaches, techniques,
methodologies, and tools used.
* The paper should report on the efficacy of the application, ideally in
comparison to alternatives, and/or what new lessons have been learned or
insights have been gained.
* Studies that report negative results must include a thorough discussion of
the possible causes of the failure and, ideally, provide a perspective on how
to address them.
Authors are encouraged to make artifacts publicly available, e.g., via a GitHub
repository or an alternative that is expected to provide long-term
availability. A respective artifact evaluation process is described below.
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**** Artefact Evaluation ****
Authors of accepted papers will be invited to submit their accompanying
artifacts (e.g., software and datasets) to the Artifact Evaluation track to be
evaluated by the Artifact Evaluation Committee. Participation in the Artifact
Evaluation process is optional and does not affect paper acceptance.
Submissions that successfully pass the Artifact Evaluation process will be
awarded a seal of approval that will be attached to the papers.
**** Special Issue in SoSyM ****
Authors of best papers from the conference will be invited to revise and submit
extended versions of their papers for publication in the Journal of Software
and Systems Modeling.
https://www.sosym.org/
