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Software and Systems Modeling
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Software and Systems Modeling - Theme Section: Large Language Models for Generative Software Engineering

Editors
Riccardo Rubei
riccardo.rubei@univaq.it
University of L’Aquila, Italy


Antonio Cicchetti
antonio.cicchetti@mdu.se
Mälardalen University, Sweden


José Antonio Hernández López
joseantonio.hernandez6@um.es
University of Murcia, Spain

The introduction of ChatGPT, Google's Gemini, and Github's Copilot marked a significant advancement in the field of natural language processing, contributing to the widespread popularity of large language models (LLMs). These models have found successful applications in diverse sectors, including healthcare, finance, education, and various engineering fields, among others.
LLMs tailored for code, such as CodeLLama, Codex, and others, have revolutionized the landscape of software engineering. They significantly enhance developers' efficiency in several classical software engineering tasks like coding, testing, and documentation. LLMs are modifying how we interact with computers, and their application to software engineering holds immense potential.


This theme section will attract innovative works aiming to explore how these powerful models can be harnessed to automate, augment, and even transform the software development lifecycle, leading to increased productivity, innovative solutions, and a new era of software creation. Hence, the primary objective of this theme section is to explore potential applications where LLMs can support
software engineers and modelers. Model-driven Engineering (MDE) can benefit from the adoption of these cutting-edge technologies and can offer methodologies to develop, optimize and improve them.


The Journal of Software and Systems Modeling (SoSyM) invites original, high-quality submissions for its theme section on “Large Language Models for Generative Software Engineering” focusing on related topics, including:

  • LLM-augmented modeling tools
  • LLMs to support MDE tasks
  • Prompt engineering techniques to adapt LLMs in the context of MDE
  • Retrieval Augmentation Generation (RAG) to support MDE
  • Performance evaluation of LLMs in a MDE context
  • Benchmarks to assess the modeling capabilities of LLMs
  • LLMs trained with modeling corpora
  • LLM agents for software modeling
  • Positive and negative findings related to real-case scenarios
  • Primary SLR concerning the interplay between LLMs and MDE

General Author Information

  • Papers must be written in a scientifically rigorous manner with adequate references to related work.
  • Submitted papers must not be simultaneously submitted in an extended form or in a shortened form to other journals or conferences. It is however possible to submit extended versions of previously published work. Manuscripts in which at least 75% of the content appears in a non-journal publication or in which at least 40% appears in a journal publication will not be published. Please see the SoSyM Policy Statement on Plagiarism for further conditions.
  • Submitted papers do not need to adhere to a particular format or page limit. Please consult the SoSyM author information for submitting papers for more details.
  • Each paper will be reviewed by at least three reviewers.

Making a Submission

  • Communicate your intent to submit a paper by emailing the theme section editors the following information before the Intent to Submit deadline:
    Title, Authors, and an Abstract.
  • Possible submission formats are:
    o Word (.doc, without macros)
    o Rich Text Format (.rtf)
    o PostScript (.ps, special fonts must be embedded)
    o PDF (saved as readable in version 5.0 or earlier)
  • Due to a change of the online submission system of SoSyM, details on how to submit your work will follow after the intent to submit deadline.

Important Dates

Intent to Submit: 15-Oct-2025

Paper submission: 15-Feb-2026

Notification: 15-Apr-2026


Further Information

If you have any questions or require additional information about this theme section, please contact the editors.

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