发表机构
University of Liechtenstein; University of Innsbruck（列支敦士登大学; 因斯布鲁克大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文扩展了可持续研究软件的适应度函数框架，引入环境和安全两组函数，将评估从FAIR合规拓宽至涵盖环境责任与长期安全的多维可持续性。
AI 中文摘要
研究软件的可持续性通常通过FAIR原则进行评估：可发现性、可访问性、互操作性和可重用性。尽管这些原则很重要，但FAIR并未涵盖所有相关的可持续性问题。研究软件还应在环境方面负责任，并随时间保持安全。过度的资源消耗会增加环境成本，而不安全的软件则会造成维护开销、技术债务和重用障碍。为此，在本文中，我们将先前提出的可持续研究软件适应度函数框架扩展到FAIR之外。我们引入了两组额外的适应度函数：环境函数，针对资源效率和执行足迹；安全函数，针对依赖健康、漏洞暴露和安全配置。这些函数共同将持续软件评估从FAIR合规性拓宽到更全面的可持续性视角。由此产生的框架将研究软件可持续性视为一个多维属性，包括FAIR、环境责任和长期安全。
英文摘要
Research software sustainability is often assessed through the FAIR principles: findability, accessibility, interoperability and reusability. While important, FAIR does not cover all relevant sustainability concerns. Research software should also be environmentally responsible and secure over time. Excessive resource consumption increases environmental cost, while insecure software creates maintenance overhead, technical debt and barriers to reuse. To this end, in this paper, we extend a previously proposed fitness function framework for sustainable research software beyond FAIR. We introduce two additional sets of fitness functions: environmental functions targeting resource efficiency and execution footprint, and security functions targeting dependency health, vulnerability exposure and secure configuration. Together, these functions broaden continuous software assessment from FAIR compliance to a more complete view of sustainability. The resulting framework treats research software sustainability as a multidimensional property that includes FAIR, environmental responsibility and long-term security.
