ds-systematic-debugging

To debug metric discrepancies, reproduce the mismatch and trace backward through joins, filters, and windowing to find where values first diverge. This evidence-first approach avoids speculative fixes by locating the exact broken transformation.

Sample ratio mismatch and metric drift stem from hidden filters, join cardinality explosions, or timezone windowing errors. Line-by-line pattern comparison against a known-working reference isolates the specific transformation causing the failure.

Trace missing rows and join cardinality errors by reproducing the discrepancy and testing minimal hypotheses. Compare row counts and unique units line-by-line against a working reference to pinpoint the first broken transformation without speculative patches.

The best way to resolve stale notebook state conflicts is a phase-based root-cause investigation that validates evidence before applying one fix per rerun. This disciplined workflow traces mismatches backward to the first broken transformation.

Yes, systematic debugging works for timezone and window boundary errors by enforcing evidence-based validation across multi-step CTE pipelines. It reproduces the mismatch and traces backward through windowing logic to identify where unit alignment fails.