Worked on the volcengine/verl repository to enhance reliability in data analysis and machine learning workflows by addressing a critical bug in the metrics calculation logic. Focused on defensive programming in Python, the developer implemented an early return path in the calculate_debug_metrics function to handle cases where the response_mask is entirely False, preventing runtime crashes during extreme rejection sampling. This solution preserved API compatibility and maintained existing usage patterns while improving code health through pre-commit checks and Ruff formatting. The work ensured that edge-case scenarios are handled gracefully, contributing to more robust and resilient data processing pipelines without introducing new features.