systematic-debugging

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Use 4-phase root cause analysis (Observe, Hypothesize, Verify, Fix); avoid unverified patches.

AI & Automation 103 stars 25 forks Updated today MIT

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Skill Content

# Systematic Debugging ## Overview The core of systematic debugging is: **understand first, then fix**. When encountering a bug, clarify symptoms, reproduction conditions, and blast radius. Draw hypotheses, verify them with experiments to isolate the root cause, and only then submit a minimal, verifiable fix. ## Ironclad Rules 1. **No random patching**: Do not submit fixes without root cause evidence. 2. **Change one variable at a time**: Prevent unexplainable results from touching multiple areas at once. 3. **Fixes MUST include evidence**: Include reproduction steps, verification, and regression results. ## When to Use - Hotfix incident response. - Flaky tests. - Cross-module anomalies that aren't intuitively obvious. - Any "fixed but I don't know why" risk scenarios. ## Four-Phase Process ### Phase 1: Observe - Precisely record error messages, timestamps, and input conditions. - Create a Minimal Reproducible Example (MRE). - Mark the blast radius (affected modules/users). ### Phase 2: Hypothesize - Propose 1–3 testable root cause hypotheses. - Design "falsifiable" checks for each hypothesis. - Prioritize high-probability, low-cost verifiable items. ### Phase 3: Verify - Run experiments and retain output logs. - Adjust only one variable to confirm causality. - Remove falsified hypotheses to converge on the most likely root cause. ### Phase 4: Fix - Implement a Minimal Fix. - Add a Regression Test. - Verify: The original error disappears AND existing behavior i...

Details

Author
KbWen
Repository
KbWen/agentic-os
Created
3 months ago
Last Updated
today
Language
Python
License
MIT

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