systematic-debugging

Systematic Debugging

The Iron Law

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

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

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

When to Use

Use for ANY technical issue:

• Test failures
• Bugs in production
• Unexpected behavior
• Performance problems
• Build failures
• Integration issues

ESPECIALLY when:

• Under time pressure (rushing = thrashing)
• "Quick fix" seems obvious
• You've already tried multiple fixes
• Previous fix didn't work

The Four Phases

┌────────────────────────────────────────────────────────────┐
│                                                            │
│  Phase 1         Phase 2         Phase 3         Phase 4   │
│  ┌───────┐      ┌─────────┐     ┌────────────┐  ┌───────┐ │
│  │ ROOT  │ ───► │ PATTERN │ ──► │ HYPOTHESIS │─►│  FIX  │ │
│  │ CAUSE │      │ ANALYSIS│     │   TEST     │  │       │ │
│  └───────┘      └─────────┘     └────────────┘  └───────┘ │
│                                                            │
└────────────────────────────────────────────────────────────┘

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Carefully

Don't skip past errors or warnings
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 HEAD~5
git log --oneline -10

What changed that could cause this?

4. Trace Data Flow

Where does bad value originate?

Error at line 50
  ↑ Called from line 30 with bad value
    ↑ Value set at line 15
      ↑ ROOT CAUSE: Missing validation at line 10

Fix at source, not at symptom.

5. Gather Evidence (Multi-Component Systems)

# Layer 1: Input
echo "=== Input data: ==="
echo "$INPUT"

# Layer 2: Processing
echo "=== After processing: ==="
echo "$PROCESSED"

# Layer 3: Output
echo "=== Final output: ==="
echo "$OUTPUT"

Run once → see WHERE it breaks → investigate that layer.

Phase 2: Pattern Analysis

Find the pattern before fixing:

1. Find Working Examples

   • Similar working code in same codebase?
   • What works that's similar to what's broken?

2. Compare Against References

   • Read reference implementation COMPLETELY
   • Don't skim - read every line

3. Identify Differences

   • What's different between working and broken?
   • List EVERY difference, however small

Phase 3: Hypothesis and Testing

Scientific method:

1. Form Single Hypothesis

   "I think X is the root cause because Y"
   

   Write it down. Be specific.

2. Test Minimally

   • SMALLEST possible change to test hypothesis
   • One variable at a time
   • Don't fix multiple things at once

3. Verify Before Continuing

   • Worked? → Phase 4
   • Didn't work? → NEW hypothesis
   • DON'T add more fixes on top

Phase 4: Implementation

Fix the root cause, not the symptom:

1. Create Failing Test

   • Simplest possible reproduction
   • MUST have before fixing
   • Use test-driven-development skill

2. Implement Single Fix

   • Address root cause identified
   • ONE change at a time
   • No "while I'm here" improvements

3. Verify Fix

   • Test passes?
   • No other tests broken?
   • Issue actually resolved?

4. If 3+ Fixes Failed: STOP

   Pattern indicating architectural problem:

   • Each fix reveals new problem elsewhere
   • Fixes require "massive refactoring"
   • Each fix creates new symptoms

   Question fundamentals:

   • Is this pattern sound?
   • Should we refactor architecture vs. continue fixing?

   Discuss with user before attempting more fixes

Red Flags - STOP and Return to Phase 1

• "Quick fix for now, investigate later"
• "Just try changing X and see"
• "Add multiple changes, run tests"
• "I don't fully understand but this might work"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)

Quick Reference

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

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