During July 2025, Andrew Tong focused on enhancing autograding reliability in the PrairieLearn/PrairieLearn repository by addressing a key issue with traceback handling in Python-based Jupyter notebook executions. He implemented a targeted patch to the Python autograder’s line caching mechanism for ipynb files, ensuring that error tracebacks now accurately reference the correct notebook source lines. This backend development work, primarily using Python, improved the debugging experience for students and reduced confusion during notebook execution. Andrew also introduced dedicated tests around notebook execution to prevent regressions, demonstrating a thoughtful approach to quality assurance and maintainability within the autograding infrastructure.