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name: systematic-debugging description: Four-phase debugging process - root cause investigation, pattern analysis, hypothesis testing, implementation.

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

CopyNO 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 in production
• Unexpected behavior
• Performance problems
• Build failures
• Integration issues

Use this 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

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, recent commits
   • New dependencies, config changes
   • Environmental differences

4. Gather Evidence in Multi-Component Systems

   CopyFor EACH component boundary:
   - Log what data enters component
   - Log what data exits component
   - Verify environment/config propagation
   - Check state at each layer
   
   Run once to gather evidence showing WHERE it breaks
   THEN analyze evidence to identify failing component
   

5. Trace Data Flow

   • Where does bad value originate?
   • What called this with 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
   • What works that's similar to what's broken?

2. Compare Against References

   • If implementing pattern, 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

1. Form Single Hypothesis

   • State clearly: "I think X is the root cause because Y"
   • Write it down
   • Be specific, not vague

2. Test Minimally

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

3. Verify Before Continuing

   • Did it work? Yes → Phase 4
   • Didn't work? Form NEW hypothesis
   • DON'T add more fixes on top

Phase 4: Implementation

1. Create Failing Test Case

   • Simplest possible reproduction
   • Automated test if possible
   • MUST have before fixing

2. Implement Single Fix

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

3. Verify Fix

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

4. If Fix Doesn't Work

   • STOP
   • Count: How many fixes have you tried?
   • If < 3: Return to Phase 1, re-analyze
   • If ≥ 3: STOP and question the architecture

5. If 3+ Fixes Failed: Question Architecture Pattern indicating architectural problem:

   • Each fix reveals new shared state/coupling
   • Fixes require "massive refactoring"
   • Each fix creates new symptoms elsewhere

   Discuss with your human partner 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"
• "I don't fully understand but this might work"
• Proposing solutions before tracing data flow
• "One more fix attempt" (when already tried 2+)

ALL of these mean: STOP. Return to Phase 1.

Common Rationalizations

Quick Reference

Real-World Impact

From debugging sessions:

• 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

Attribution

Based on obra/superpowers systematic-debugging skill.