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This PR improves performance of boolean value counting in validation (i.e., tallying up passing/failing test units). I replaced the Python list-based counting with native DataFrame filtering operations for counting True/False values. This avoids extracting potentially large columns into Python lists and leverages the DataFrame library's optimized filtering capabilities. These changes maintain identical functionality while improving performance for large datasets