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@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}, abstract = {Feature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serialising feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents , a repository of feature models in UVL format. provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo –one of the most well-known open science repositories– providing a permanent save of datasets and following open science principles. includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling.} }

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 AB - Feature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serialising feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents , a repository of feature models in UVL format. provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo –one of the most well-known open science repositories– providing a permanent save of datasets and following open science principles. includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling. ER -

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) Abstract: Feature models are the de facto standard for modelling variabilities and commonalities in features and relationships in software product lines. They are the base artefacts in many engineering activities, such as product configuration, derivation, or testing. Concrete models in different domains exist; however, many are in private or sparse repositories or belong to discontinued projects. The dispersion of knowledge of feature models hinders the study and reuse of these artefacts in different studies. The Universal Variability Language (UVL) is a community effort textual feature model language that promotes a common way of serialising feature models independently of concrete tools. Open science principles promote transparency, accessibility, and collaboration in scientific research. Although some attempts exist to promote feature model sharing, the existing solutions lack open science principles by design. In addition, existing and public feature models are described using formats not always supported by current tools. This paper presents , a repository of feature models in UVL format. provides a front end that facilitates the search, upload, storage, and management of feature model datasets, improving the capabilities of discontinued proposals. Furthermore, the tool communicates with Zenodo –one of the most well-known open science repositories– providing a permanent save of datasets and following open science principles. includes existing datasets and is readily available to include new data and functionalities in the future. It is maintained by three active universities in variability modelling. 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) Abstract: Feature modelling is a cornerstone of software product line engineering, providing a means to represent software variability through features and their relationships. Since its inception in 1990, feature modelling has evolved through various extensions, and after three decades of development, there is a growing consensus on the need for a standardised feature modelling language. Despite multiple endeavours to standardise variability modelling and the creation of various textual languages, researchers and practitioners continue to use their own approaches, impeding effective model sharing. In 2018, a collaborative initiative was launched by a group of researchers to develop a novel textual language for representing feature models. This paper introduces the outcome of this effort: the Universal Variability Language (UVL), which is designed to be human-readable and serves as a pivot language for diverse software engineering tools. The development of UVL drew upon community feedback and leveraged established literature in the field of variability modelling. The language is structured into three levels – Boolean, Arithmetic, and Type – and allows for language extensions to introduce additional constructs enhancing its expressiveness. UVL is integrated into various existing software tools, such as FeatureIDE and flamapy, and is maintained by a consortium of institutions. All tools that support the language are released in an open-source format, complemented by dedicated parser implementations for Python and Java. Beyond academia, UVL has found adoption within a range of institutions and companies. It is envisaged that UVL will become the language of choice in the future for a multitude of purposes, including knowledge sharing, educational instruction, and tool integration and interoperability. We envision UVL as a pivotal solution, addressing the limitations of prior attempts and fostering collaboration and innovation in the domain of software product line engineering. 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