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Practical software engineering for software-writing scientists.

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This tutorial introduces software engineering techniques like version control and testing to improve scientific software. These practices enhance reproducibility, maintainability, and collaboration in research tools.

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Area of Science:

  • Scientific computing
  • Computational chemistry
  • Chemical physics

Background:

  • Software is integral to scientific research for modeling and data analysis.
  • Long-lived and complex scientific software projects face challenges in maintainability and reproducibility.

Purpose of the Study:

  • To introduce practical software engineering techniques for scientists.
  • To address challenges in complexity, maintainability, and reproducibility of scientific software.
  • To promote sustainable, transparent, and collaborative scientific software development.

Main Methods:

  • Introduction of software engineering techniques: version control, testing, documentation, continuous integration, and packaging.
  • Drawing on principles from software evolution.
  • Tailored discussion for scientists without formal software engineering training.
  • Examples from the chemical physics community.

Main Results:

  • Demonstration of how software engineering principles benefit scientific projects and communities.
  • Reflection on the role of large language models in scientific software development.
  • Presentation of approachable, widely adopted practices.

Conclusions:

  • Adoption of software engineering practices leads to more robust and sustainable scientific software.
  • Effective software engineering enhances the transparency and collaborative potential of research tools.
  • Continuous learning and adaptation, including leveraging AI, are key for future scientific software development.