David Romero-Organvidez , José A. Galindo , Chico Sundermann , Jose-Miguel Horcas , David Benavides
{"title":"UVLHub:使用 UVL 和开放科学原则的特征模型数据存储库","authors":"David Romero-Organvidez , José A. Galindo , Chico Sundermann , Jose-Miguel Horcas , David Benavides","doi":"10.1016/j.jss.2024.112150","DOIUrl":null,"url":null,"abstract":"<div><p>Feature models are the <em>de facto</em> 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 serializing 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 <figure><img></figure> , a repository of feature models in UVL format. <figure><img></figure> 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. <figure><img></figure> 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.</p></div>","PeriodicalId":51099,"journal":{"name":"Journal of Systems and Software","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S016412122400195X/pdfft?md5=2c04f3c6d777710e69a0d2ddb2012e6a&pid=1-s2.0-S016412122400195X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"UVLHub: A feature model data repository using UVL and open science principles\",\"authors\":\"David Romero-Organvidez , José A. Galindo , Chico Sundermann , Jose-Miguel Horcas , David Benavides\",\"doi\":\"10.1016/j.jss.2024.112150\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Feature models are the <em>de facto</em> 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 serializing 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 <figure><img></figure> , a repository of feature models in UVL format. <figure><img></figure> 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. <figure><img></figure> includes existing datasets and is readily available to include new data and functionalities in the future. 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UVLHub: A feature model data repository using UVL and open science principles
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 serializing 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.
期刊介绍:
The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to:
• Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution
• Agile, model-driven, service-oriented, open source and global software development
• Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems
• Human factors and management concerns of software development
• Data management and big data issues of software systems
• Metrics and evaluation, data mining of software development resources
• Business and economic aspects of software development processes
The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.