debug

Root cause analysis for debugging is a structured workflow to find the true underlying fault causing unexpected behavior or failing tests. Use it when superficial symptom fixes fail to resolve recurring runtime exceptions or test failures across codebases.

Debug a failing test by first reproducing the exact error trace, then generate two to three distinct hypotheses for the root cause. Gather targeted evidence for each hypothesis before changing code to ensure the fix resolves the entire class of failures.

The best way to diagnose runtime exceptions is to follow call chains upward and trace data origins backward. Use git history or blame to clarify code intent, then apply the Five Whys technique to escalate from the symptom to the faulty design assumption.

Yes, you can use git blame and history to understand code intent when diagnosing unexpected production behavior. Tracing recent code changes helps establish reliable reproduction steps and provides context for generating accurate root cause hypotheses.

Scope a minimal fix by classifying potential changes as in-scope, adjacent, or out-of-scope. Weigh the trade-offs of each approach, request user approval when appropriate, and aim for the smallest validated change that resolves the whole class of failures.

Root cause analysis finds symptoms instead of faults when it skips reproduction or fails to generate distinct hypotheses. Require exact error output reproduction, trace data origins backward, and apply the Five Whys to escalate from superficial symptoms to the true design assumption.