Worked on the NEONScience/NEON-IS-data-processing repository to enhance the project’s testing framework, focusing on integrating unit testing libraries and coverage reporting. Leveraged R and YAML to update the CI/CD pipeline, enabling automated generation of detailed test reports. This improvement established a foundation for higher code quality and more reliable data processing by providing faster feedback on code changes. The approach emphasized robust testing practices and streamlined continuous integration workflows, ensuring that future development can be validated efficiently. No bugs were addressed during this period, with efforts concentrated on building out the testing infrastructure and improving maintainability through better test coverage.