systematic-debugging
SolidUse 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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# 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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