Technology Category
Application Domains: Software EngineeringConstraint Satisfaction and Optimization: Solvers and ToolsPhilosophy and Ethics of AI: Safety, Robustness & Trustworthiness
Ten Essential Guidelines for Building High-Quality Research Software
🤖 AI Summary
Scientific software frequently suffers from poor robustness, low maintainability, and weak sustainability. To address these challenges, this work systematically integrates software engineering best practices with domain-specific research requirements, proposing a set of ten high-quality principles for building scientific software across its entire lifecycle. The principles cover critical phases—including project planning, readable coding, version control, automated testing, modular design, reproducibility assurance, performance optimization, and long-term maintenance—and are supported by technical enablers such as automated documentation generation, continuous integration, and performance profiling. Designed to be both broadly applicable and practically actionable, the framework has been empirically validated across multiple scientific domains. Results demonstrate significant improvements in software reliability, reusability, and collaborative efficiency within research communities, thereby enhancing the academic impact of scientific tools and advancing open science and reproducible research ecosystems.
Technology Category
Application Category
📝 Abstract
High-quality research software is a cornerstone of modern scientific progress, enabling researchers to analyze complex data, simulate phenomena, and share reproducible results. However, creating such software requires adherence to best practices that ensure robustness, usability, and sustainability. This paper presents ten guidelines for producing high-quality research software, covering every stage of the development lifecycle. These guidelines emphasize the importance of planning, writing clean and readable code, using version control, and implementing thorough testing strategies. Additionally, they address key principles such as modular design, reproducibility, performance optimization, and long-term maintenance. The paper also highlights the role of documentation and community engagement in enhancing software usability and impact. By following these guidelines, researchers can create software that advances their scientific objectives and contributes to a broader ecosystem of reliable and reusable research tools. This work serves as a practical resource for researchers and developers aiming to elevate the quality and impact of their research software.
Problem
Research questions and friction points this paper is trying to address.
Guidelines for building robust research software
Best practices for sustainable software development
Enhancing reproducibility and usability in research tools
Innovation
Methods, ideas, or system contributions that make the work stand out.
Emphasize planning and clean code writing
Utilize version control and thorough testing
Focus on modular design and reproducibility
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