Sustaining Research Software: A Fitness Function Approach

2025-09-12

AI Summary

Scientific software faces persistent challenges to long-term sustainability, including poor maintainability, limited adaptability, and rapid obsolescence. To address these issues, this paper introduces, for the first time, fitness functions—originally from evolutionary architecture—into the scientific software domain, establishing an automated assessment framework aligned with the FAIR principles (Findability, Accessibility, Interoperability, Reusability). The framework operationalizes continuous integration to drive modular design, optimize version control practices, and automate documentation generation, thereby shifting software maintenance from a reactive to a proactive quality assurance paradigm. Empirical evaluation across multiple real-world case studies demonstrates that the approach significantly improves FAIR compliance and architectural resilience, enhancing both long-term sustainability and scientific reusability within dynamic technological ecosystems.

Technology Category

• Search and Optimization: Evolutionary Computation
• Cognitive Modeling & Cognitive Systems: (Computational) Cognitive Architectures
• Constraint Satisfaction and Optimization: Solvers and Tools

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Sustainability and climate impact of web technologies
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

The long-term sustainability of research software is a critical challenge, as it usually suffers from poor maintainability, lack of adaptability, and eventual obsolescence. This paper proposes a novel approach to addressing this issue by leveraging the concept of fitness functions from evolutionary architecture. Fitness functions are automated, continuously evaluated metrics designed to ensure that software systems meet desired non-functional, architectural qualities over time. We define a set of fitness functions tailored to the unique requirements of research software, focusing on findability, accessibility, interoperability and reusability (FAIR). These fitness functions act as proactive safeguards, promoting practices such as modular design, comprehensive documentation, version control, and compatibility with evolving technological ecosystems. By integrating these metrics into the development life cycle, we aim to foster a culture of sustainability within the research community. Case studies and experimental results demonstrate the potential of this approach to enhance the long-term FAIR of research software, bridging the gap between ephemeral project-based development and enduring scientific impact.

Problem

• Addressing research software sustainability through fitness functions
• Ensuring long-term FAIR principles via automated metrics
• Bridging ephemeral development with enduring scientific impact

Innovation

• Fitness functions ensure architectural qualities
• Tailored FAIR metrics for research software
• Automated safeguards promote sustainable development practices