A first prototype of a new repository for feature model exchange and knowledge sharing

David D. Romero, J. Galindo, J. Horcas, David Benavides
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引用次数: 2

Abstract

Feature models are the "de facto" standard for variability modelling and are used in both academia and industry. The MODEVAR initiative tries to establish a common textual feature modelling language that can be used by different communities and can allow information sharing. Feature model related researches use different models for different purposes such as analysis, sampling, testing, debugging, teaching, etc. Those models are shared in private repositories and there is a risk that all that knowledge is spread across different platforms which hinder collaboration and knowledge reuse. In this paper, we propose a first working version of a new feature model repository that allows to centralise the knowledge generated in the community together with advanced capabilities such as DOI generation, an API, analysis reports, among others. Our solution is a front end interface that uses the popular open science repository Zenodo as an end point to materialise the storage of all the information. Zenodo is enhanced with characteristics that facilitate the management of the models. The idea of our repository is to provide existing but also new features that are not present in other repositories (e.g., SPLOT). We propose to populate our repository with all the existing models of many sources including SPLOT.
用于特征模型交换和知识共享的新存储库的第一个原型
特征模型是可变性建模的“事实上的”标准,在学术界和工业界都有使用。MODEVAR计划试图建立一种通用的文本特征建模语言,供不同的社区使用,并允许信息共享。特征模型相关研究针对不同的目的,如分析、采样、测试、调试、教学等,使用不同的模型。这些模型在私有存储库中共享,并且存在这样的风险,即所有这些知识都分布在不同的平台上,这会阻碍协作和知识重用。在本文中,我们提出了一个新特性模型存储库的第一个工作版本,它允许将社区中生成的知识与高级功能(如DOI生成、API、分析报告等)集中在一起。我们的解决方案是一个前端接口,它使用流行的开放科学存储库Zenodo作为端点来实现所有信息的存储。Zenodo增强了便于模型管理的特性。我们的存储库的想法是提供现有的和其他存储库(例如SPLOT)中没有的新特性。我们建议用包括SPLOT在内的许多源代码的所有现有模型填充我们的存储库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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