No result found

Please try again with a different query

Mode

Light

Dark

System

Cite us!

Download all

UVL

Glencoe

DIMACS

SPLOT

Download

Explore

Dashboard

Team

Generate models

Let's get started!

Login

Sign up

v2.7.5

Generalized Feature Trees (GFTs)

1. Home
2. Generalized Feature Trees (GFTs)
3. Truck_gft.uvl

Generalized Feature Trees (GFTs)

Journal Article

Oct 02, 2025 · 12 models · 3.68 MB

Authors

José Miguel Horcas

Universidad de Málaga

Joaquín Ballesteros

Universidad de Málaga

Mónica Pinto

Universidad de Málaga

Lidia Fuentes

Universidad de Málaga

Description

This dataset contains Generalized Feature Trees (GFTs) for several well-known feature models. A GFT is a representation of a feature model where all cross-tree constraints have been integrated directly into the feature tree structure itself, maintaining the semantics of the feature model (i.e., maintaining the same set of products). This refactoring eliminates explicit cross-tree constraints, allowing a feature to appear multiple times within the tree (in exclusive branches) to represent different valid configurations.

Show more

Tags

Generalized Feature Tree GFT constraint refactoring cross-tree constraint sans-constraints FMSans

Identifier

DOI /doi/10.5281/zenodo.17252231

http://www.uvlhub.io/doi/10.5281/zenodo.17252231

Actions

Download dataset

UVL

Glencoe

DIMACS

SPLOT

Download

Model Truck_gft.uvl

— / 12

21.98 KB

• UVL
• Glencoe
• DIMACS
• SPLOT

Open with

Collapse zero values

Collapse sub-properties

Open with

Metric Details

Copy

Dataset QR

Download as PNG SVG JPG

2025© University of Seville · University of Malaga · University of Ulm

•  Repository on GitHub

@article{romero2024_uvlhub_open_science,
    title = {UVLHub: A feature model data repository using UVL and open science principles},
    journal = {Journal of Systems and Software},
    pages = {112150},
    year = {2024},
    issn = {0164-1212},
    doi = {https://doi.org/10.1016/j.jss.2024.112150},
    url = {https://www.sciencedirect.com/science/article/pii/S016412122400195X},
    author = {David Romero-Organvidez and José A. Galindo and Chico Sundermann and Jose-Miguel Horcas and David Benavides},
    keywords = {Feature models, Software product line, Variability, Dataset, Uvl}
}

TY  - JOUR
T1  - UVLHub: A feature model data repository using UVL and open science principles
AU  - Romero-Organvidez, David
AU  - Galindo, José A.
AU  - Sundermann, Chico
AU  - Horcas, Jose-Miguel
AU  - Benavides, David
JO  - Journal of Systems and Software
SP  - 112150
PY  - 2024
DA  - 2024/07/01/
SN  - 0164-1212
DO  - https://doi.org/10.1016/j.jss.2024.112150
UR  - https://www.sciencedirect.com/science/article/pii/S016412122400195X
KW  - Feature models
KW  - Software product line
KW  - Variability
KW  - Dataset
KW  - Uvl

David Romero-Organvidez, José A. Galindo, Chico Sundermann, Jose-Miguel Horcas, David Benavides,
UVLHub: A feature model data repository using UVL and open science principles,
Journal of Systems and Software,
2024,
112150,
ISSN 0164-1212,
https://doi.org/10.1016/j.jss.2024.112150.
(https://www.sciencedirect.com/science/article/pii/S016412122400195X)
Keywords: Feature models; Software product line; Variability; Dataset; Uvl

Romero-Organvidez, D., Galindo, J. A., Sundermann, C., Horcas, J.-M., & Benavides, D. (2024). UVLHub: A feature model data repository using UVL and open science principles. Journal of Systems and Software, 2024, 112150. https://doi.org/10.1016/j.jss.2024.112150

@article{benavides2024uvl,
    title = {UVL: Feature modelling with the Universal Variability Language},
    journal = {Journal of Systems and Software},
    volume = {225},
    pages = {112326},
    year = {2025},
    issn = {0164-1212},
    doi = {https://doi.org/10.1016/j.jss.2024.112326},
    url = {https://www.sciencedirect.com/science/article/pii/S0164121224003704},
    author = {David Benavides and Chico Sundermann and Kevin Feichtinger and José A. Galindo and Rick Rabiser and Thomas Thüm},
    keywords = {Feature model, Software product lines, Variability},
}      

TY  - JOUR
T1  - UVL: Feature modelling with the Universal Variability Language
AU  - Benavides, David
AU  - Sundermann, Chico
AU  - Feichtinger, Kevin
AU  - Galindo, José A.
AU  - Rabiser, Rick
AU  - Thüm, Thomas
JO  - Journal of Systems and Software
VL  - 225
SP  - 112326
PY  - 2025
DA  - 2025/07/01/
SN  - 0164-1212
DO  - https://doi.org/10.1016/j.jss.2024.112326
UR  - https://www.sciencedirect.com/science/article/pii/S0164121224003704
KW  - Feature model
KW  - Software product lines
KW  - Variability

David Benavides, Chico Sundermann, Kevin Feichtinger, José A. Galindo, Rick Rabiser, Thomas Thüm,
UVL: Feature modelling with the Universal Variability Language,
Journal of Systems and Software,
Volume 225,
2025,
112326,
ISSN 0164-1212,
https://doi.org/10.1016/j.jss.2024.112326.
(https://www.sciencedirect.com/science/article/pii/S0164121224003704)
Keywords: Feature model; Software product lines; Variability

Benavides, D., Sundermann, C., Feichtinger, K., Galindo, J. A., Rabiser, R., & Thüm, T. (2025). UVL: Feature modelling with the Universal Variability Language. Journal of Systems and Software, 225, 112326. https://doi.org/10.1016/j.jss.2024.112326