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.

Violating the letter of this process is violating the spirit of debugging.

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 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
• You don't fully understand the issue

The Four Phases

You MUST 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 or warnings
   • They often contain the exact solution
   • Read stack traces completely
   • Note line numbers, file paths, error codes

2. Reproduce Consistently

   • Can you trigger it reliably?
   • What are the exact steps?
   • Does it happen every time?
   • If not reproducible → gather more data, don't guess

3. Check Recent Changes

   • What changed that could cause this?
   • Git diff, recent commits
   • New dependencies, config changes

4. Gather Evidence in Multi-Component Systems

   WHEN system has multiple components: Add diagnostic instrumentation at each component boundary:

   • Log what data enters component
   • Log what data exits component
   • Verify environment/config propagation
   • Run once to gather evidence showing WHERE it breaks

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
2. Compare Against References - Read reference implementation COMPLETELY
3. Identify Differences - List every difference, however small
4. Understand Dependencies - What components, settings, assumptions?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis - "I think X is the root cause because Y"
2. Test Minimally - SMALLEST possible change, one variable at a time
3. Verify Before Continuing - Didn't work? Form NEW hypothesis
4. When You Don't Know - Say "I don't understand X", ask for help

Phase 4: Implementation

1. Create Failing Test Case - Simplest possible reproduction
2. Implement Single Fix - ONE change at a time
3. Verify Fix - Test passes? No other tests broken?
4. If Fix Doesn't Work - Count fixes tried. If ≥3: STOP and question architecture
5. If 3+ Fixes Failed - Question fundamentals, discuss with human partner

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

Excuse	Reality
"Issue is simple, don't need process"	Simple issues have root causes too. Process is fast for simple bugs.
"Emergency, no time for process"	Systematic debugging is FASTER than guess-and-check thrashing.
"Just try this first, then investigate"	First fix sets the pattern. Do it right from the start.
"I'll write test after confirming fix works"	Untested fixes don't stick. Test first proves it.
"Multiple fixes at once saves time"	Can't isolate what worked. Causes new bugs.

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

Supporting Techniques

See additional files in this directory:

• root-cause-tracing.md - Trace bugs backward through call stack
• defense-in-depth.md - Add validation at multiple layers
• condition-based-waiting.md - Replace arbitrary timeouts with condition polling