systematic-debugging

name	systematic-debugging
description	Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Systematic Debugging

Overview

Random fixes waste time and create new bugs. Quick patches mask underlying issues.

Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

If you haven't completed Phase 1, you cannot propose fixes.

When to Use

Use for ANY technical issue: test failures, bugs, unexpected behavior, performance problems, build failures, integration issues.

Use ESPECIALLY when:

• Under time pressure (emergencies make guessing tempting)
• "Just one quick fix" seems obvious
• You've already tried multiple fixes
• Previous fix didn't work

The Four Phases

Complete each phase before proceeding to the next.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully — don't skip past errors. Read stack traces completely. Note line numbers, file paths, error codes.

2. Reproduce Consistently — can you trigger it reliably? What are the exact steps? If not reproducible, gather more data — don't guess.

3. Check Recent Changes — git diff, recent commits, new dependencies, config changes, environmental differences.

4. Gather Evidence in Multi-Component Systems — at EACH component boundary: log what data enters/exits, verify environment/config propagation, check state at each layer. Run once to gather evidence showing WHERE it breaks.

5. Trace Data Flow — where does the bad value originate? What called this with the bad value? Keep tracing up until you find the source. Fix at source, not at symptom.

Phase 2: Pattern Analysis

1. Find Working Examples — locate similar working code in same codebase
2. Compare Against References — read reference implementations COMPLETELY, not skimming
3. Identify Differences — list every difference, however small
4. Understand Dependencies — what components, settings, config, assumptions?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis — "I think X is the root cause because Y" — write it down, be specific
2. Test Minimally — smallest possible change, one variable at a time
3. Verify Before Continuing — worked? → Phase 4. Didn't? → new hypothesis. Don't stack fixes.

Phase 4: Implementation

1. Create Failing Test Case — simplest reproduction, automated if possible
2. Implement Single Fix — address root cause, ONE change, no "while I'm here" improvements
3. Verify Fix — test passes? No other tests broken? Issue actually resolved?
4. If 3+ Fixes Failed — STOP. Question the architecture. Each fix revealing new problems = architectural issue. Discuss before attempting more fixes.

Red Flags — STOP and Follow Process

If you catch yourself thinking:

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "Skip the test, I'll manually verify"
• "It's probably X, let me fix that"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)

ALL mean: STOP. Return to Phase 1.

Quick Reference

Phase	Key Activities	Success Criteria
1. Root Cause	Read errors, reproduce, check changes, gather evidence	Understand WHAT and WHY
2. Pattern	Find working examples, compare	Identify differences
3. Hypothesis	Form theory, test minimally	Confirmed or new hypothesis
4. Implementation	Create test, fix, verify	Bug resolved, tests pass

Real-World Impact

• Systematic approach: 15-30 minutes to fix
• Random fixes approach: 2-3 hours of thrashing
• First-time fix rate: 95% vs 40%
• New bugs introduced: Near zero vs common