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 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

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

   • What changed that could cause this?
   • Git diff, recent commits

4. 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 settings, config, environment?

Phase 3: Hypothesis and Testing

1. Form Single Hypothesis — "I think X is the root cause because Y"
2. Test Minimally — make the SMALLEST possible change: one variable at a time
3. Verify Before Continuing — did it work? Yes → Phase 4; No → form NEW hypothesis
4. When You Don't Know — say "I don't understand X", don't pretend to know

Phase 4: Implementation

1. Create Failing Test Case — MUST have before fixing (use test-driven-development skill)
2. Implement Single Fix — address the root cause, ONE change at a time
3. Verify Fix — test passes? Other tests unbroken?
4. If 3+ Fixes Failed — STOP and question the architecture

Red Flags — STOP and Follow Process

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "Add multiple changes, run tests"
• "It's probably X, let me fix that"
• 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.
"Emergency, no time for process"	Systematic debugging is FASTER than guess-and-check.
"Just try this first, then investigate"	First fix sets the pattern. Do it right.
"I see the problem, let me fix it"	Seeing symptoms ≠ understanding root cause.
"One more fix attempt" (after 2+)	3+ failures = architectural problem.

Quick Reference

Phase	Key Activities	Success Criteria
1. Root Cause	Read errors, reproduce, check changes	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%