SEMODS: A Validated Dataset of Open-Source Software Engineering Models (November 2025 Snapshot)

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Authors: Alexandra González Álvarez, Xavier Franch, Silverio Martínez‐Fernández
Cited by: 0

Abstract

This dataset accompanies the paper "SEMODS: A Validated Dataset of Open-Source Software Engineering Models", accepted at the 3rd ACM International Conference on AI Foundation Models and Software Engineering (FORGE 2026) Dataset Description SEMODS (Software Engineering MODels) is a validated dataset comprising 3,427 open-source software engineering models hosted on Hugging Face. It provides a structured view of the SE model ecosystem as of November 2025, addressing the lack of SE-specific catalogues in generalist model registries. It offers a standardized representation of model evaluation results and supports multiple applications such as data analysis, model discovery, benchmarking, and model adaptation. The dataset is provided as a PostgreSQL dump file. Important: The dump was created using PostgreSQL 17. Users must restore it using PostgreSQL server and client tools version 17 or newer. Dumps created with newer PostgreSQL versions are not backward compatible. How to load the database locally Install and start PostgreSQL 17: brew install postgresql@17 brew services start postgresql@17 2. Create the database: /opt/homebrew/opt/postgresql@17/bin/createdb semods 3. Restore the dump (Replace /path/to/ with the actual path to your downloaded file) /opt/homebrew/opt/postgresql@17/bin/pg_restore -d semods /path/to/SEMODS_202511.dump Alternatively, you can use graphical tools such as DBeaver by connecting to a PostgreSQL 17 instance and using the "Restore" option. Citation Please cite the associated FORGE 2026 paper when using this dataset: @article{gonzalez2026semods, title={SEMODS: A Validated Dataset of Open-Source Software Engineering Models}, author={Gonz{\'a}lez, Alexandra and Franch, Xavier and Mart{\'\i}nez-Fern{\'a}ndez, Silverio}, journal={arXiv preprint arXiv:2601.00635}, year={2026}}

Fields of Study & Subjects

Software Engineering Research Software Engineering Techniques and Practices Open Source Software Innovations

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
19 January 2026
Document type
Dataset