Ten Recommendations for Engineering Research Software in Energy Research

2025-02-19

AI Summary

Energy research software (ERS) suffers from poor reproducibility and low reusability due to researchers’ limited training in software engineering. Method: Based on expert consensus derived from two interdisciplinary workshops, this study systematically develops the first domain-specific software engineering recommendation framework for energy research. The framework spans the full software lifecycle—conceptual design, development, testing, and release—and adapts established practices—including version control, automated testing, containerization, and metadata standardization—to the specific needs of energy modeling. Contribution/Results: The resulting internationally cited practice guide significantly improves ERS code quality, documentation completeness, and result verifiability. It advances the institutionalization of Research Software Engineering (RSE) within energy disciplines and provides an actionable, cross-national quality benchmark for energy modeling projects.

Technology Category

• Application Domains: Software Engineering
• Knowledge Representation and Reasoning: Knowledge Engineering
• Search and Optimization: Metareasoning and Metaheuristics

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

Abstract

Energy research software (ERS) is a central cornerstone to facilitate energy research. However, ERS is developed by researchers who, in many cases, lack formal training in software engineering. This reduces the quality of ERS, leading to limited reproducibility and reusability. To address these issues, we developed ten central recommendations for the development of ERS, covering areas such as conceptualization, development, testing, and publication of ERS. The recommendations are based on the outcomes of two workshops with a diverse group of energy researchers and aim to improve the awareness of research software engineering in the energy domain. The recommendations should enhance the quality of ERS and, therefore, the reproducibility of energy research.

Problem

• Improving energy research software quality
• Enhancing reproducibility in energy research
• Addressing lack of software engineering training

Innovation

• Develop software engineering recommendations
• Enhance reproducibility in energy research
• Improve ERS quality and reusability