New Ideas and Emerging Results (NIER)MODELS 2025

About

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. MODELS participants originate from a wide variety of backgrounds, including researchers, academics, engineers, and industry professionals.

MODELS 2025 is a forum for participants to share the latest research and practical experiences around modeling, modeling languages, and model-based software and systems engineering. Respective contributions advance the fundamentals of modeling and report applications of modeling in areas such as cyber-physical systems, embedded systems, socio-technical systems, cloud computing, big data, machine learning, security, open source, and sustainability.

MODELS is introducing, for the first time, the New Ideas and Emerging Results (NIER) track, aiming to provide a dedicated forum for visionary, thought-provoking, and forward-looking research in the field of model-driven engineering (MDE). This new track aims to showcase early-stage research, novel ideas, and innovative approaches that have the potential to shape the future of the discipline.

The NIER track welcomes submissions that explore bold hypotheses, unconventional methodologies, and interdisciplinary perspectives, fostering discussions that challenge the status quo and open new avenues for exploration. By including the NIER track, MODELS seeks to encourage early feedback, spark collaborations, and accelerate the adoption of groundbreaking concepts, strengthening its role as a leading venue for innovation in MDE.

Topics of Interest

MODELS 2025 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.

Call for Contributions

NIER 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 that challenge the state of the art and open new avenues for exploration. 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, explore bold hypotheses, unconventional methodologies, or apply modeling technology to unprecedented application areas.

Evaluation Criteria

New ideas and vision papers will be assessed primarily on their degree of originality and potential for advancing innovation in the field. As such, new ideas and emerging results are expected to 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. New ideas and emerging results need to be fully worked out, even if a detailed roadmap does not need to be provided.

The use of worked-out examples to support new ideas is strongly encouraged. 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.

Submission process

The submission process for the MODELS 2025 NIER Track follows a double-anonymous review process in which authors will not be identified to reviewers and reviewers will not be identified to authors. Thus, no submission may reveal the identity of its authors and authors must make every effort to comply with the double-anonymous review process.

NIER paper must not exceed 6 pages for the main text, including all figures, tables, appendices, etc. One more page containing only references is permitted. Note that the page limit applies to the final, non-anonymous version; hence a submitted version cannot exhaust the page limit unless it uses blank space for any author information that was removed.

All submissions must be in PDF format. The page limit is strict; it will not be possible to purchase additional pages at any stage of the process.

A double-anonymous review process will be used for the NIER Track. Therefore, no submission may reveal the identity of the authors. Authors must make every effort to comply with the double-anonymous review process. In particular:

• Authors’ names must not be mentioned in the submission.
• All references to the author’s previous work should be in the third person.
• While authors have the right to upload preprints on ArXiV or similar sites, they should not indicate that the manuscript was submitted to MODELS 2025.
• If data is made available to the program committee (by uploading supplemental material or a link to a repository), this data must also not reveal the identity of the authors.

Papers must be submitted electronically through the MODELS 2025 NIER EasyChair web page.

Submissions must conform to the IEEE formatting instructions.

Please note the IEEE Authors Rights and Responsibilities.

Finally, IEEE requires the use of ORCIDs. LaTeX users should use the “orcidlink” package, \hypersetup{pdfborder={0 0 0}}, and \orcidlink{XXXX-XXXX-XXXX-XXXX} after each author name.

Important Dates

All submission dates are at 23:59 AoE (Anywhere on Earth).

• Abstract Submission: July 1st, 2025
• Paper Submission: July 8th, 2025
• Author notification: August 19th, 2025
• Camera Ready Due: September 2nd, 2025

Submission deadlines are hard, i.e., there will be no submission deadline extensions.