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

Don't skip when:

• Issue seems simple (simple bugs have root causes too)
• You're in a hurry (rushing guarantees rework)

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
   • Environmental differences

4. Gather Evidence in Multi-Component Systems

   WHEN system has multiple components:

   BEFORE proposing fixes, add diagnostic instrumentation:

   For 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
   THEN investigate that specific 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

Find the pattern before fixing:

1. Find Working Examples — Locate similar working code in same codebase
2. Compare Against References — Read reference implementation COMPLETELY
3. Identify Differences — List every difference, however small
4. Understand Dependencies — What other components does this need?

Phase 3: Hypothesis and Testing

Scientific method:

1. Form Single Hypothesis — "I think X is the root cause because Y"
2. Test Minimally — Make the SMALLEST possible change to test hypothesis
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

Fix the root cause, not the symptom:

1. Create Failing Test Case — Simplest possible reproduction. MUST have before fixing.

2. Implement Single Fix — Address the root cause. ONE change at a time.

3. Verify Fix — Test passes? No other tests broken? Issue actually resolved?

4. If Fix Doesn't Work — STOP. Count fixes tried. If ≥ 3: question the architecture.

5. If 3+ Fixes Failed: Question Architecture

   • Is this pattern fundamentally sound?
   • Should we refactor architecture vs. continue fixing symptoms?
   • Discuss with user 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"
• "It's probably X, let me fix that"
• "I don't fully understand but this might work"
• "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 from the start.
"Multiple fixes at once saves time"	Can't isolate what worked. Causes new bugs.
"I see the problem, let me fix it"	Seeing symptoms ≠ understanding root cause.
"One more fix attempt" (after 2+ failures)	3+ failures = architectural problem.

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

Related skills:

• oac:verification-before-completion — Verify fix worked before claiming success
• oac:test-generation — For creating failing test cases (Phase 4, Step 1)