Academic code is often written to produce a paper and then abandoned. This creates massive technical debt when others try to build upon it.
The "Works on My Machine" Problem
Reproducibility is a core tenet of science, but code often lacks dependencies or documentation.
Solution
We advocate for applying software engineering best practices to scientific code: - Version Control: Git for everything. - Testing: Unit tests for physical models. - Containerization: Docker for reproducible environments.