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systematic-debugging

Structured debugging methodology using hypothesis-driven investigation, log analysis, and bisection to isolate and resolve defects.

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a5c-ai/babysitter
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2026년 6월 5일 18:37
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name
systematic-debugging
description
Structured debugging methodology using hypothesis-driven investigation, log analysis, and bisection to isolate and resolve defects.
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{"domains":["domain:software-engineering"],"skillAreas":["skill-area:agentic-loops","skill-area:orchestration-loop"],"workflows":["workflow:feature-development"],"topics":["topic:developer-experience"],"roles":["role:tech-lead","role:backend-engineer"]}
- Unexpected behavior discovered during testing - Bug reports require investigation - Performance issues need root cause analysis ## Process 1. **Reproduce** - Confirm the defect with a minimal reproduction 2. **Hypothesize** - Form theories about the root cause 3. **Investigate** - Systematically test hypotheses (logs, breakpoints, bisection) 4. **Isolate** - Narrow to the specific component/line 5. **Fix** - Apply targeted fix addressing root cause 6. **Verify** - Confirm fix resolves the issue without regression ## Key Rules - Never apply fixes without understanding the root cause - For Strike-3/post-instrumentation handoffs, do not apply a source-code fix until you enumerate at least 3 candidate root-cause hypotheses, give each hypothesis a falsifying log line or observation, and cite concrete log evidence for the selected fix. Use seq number when present; otherwise cite timestamp, log-id, or artifact path plus the exact log line. If no proposed fix cites a specific log line or log record, mark `needs-more-data`. - Use web-researcher agent for unfamiliar error patterns - Document the investigation path for future reference - Verify that the fix does not introduce regressions ## Tool Use Integrated into `methodologies/rpikit/rpikit-implement` (failure handling)
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