Worked on the gaelpoette/COURS_COLLAB_2024 repository to establish a foundational automated testing infrastructure for simulation features. Focused on building parameterized configuration and data provisioning systems, the work introduced standardized Python test assets and deterministic data sources to support reliable automated validation. By implementing automation testing and data management techniques, the developer enabled more consistent and maintainable test scenarios, reducing regression risk and streamlining the release process. The approach emphasized maintainability through file standardization and configuration management, ensuring future test runs are efficient and reproducible. This effort laid the groundwork for robust simulation testing using Python and automation best practices.