Code Debug

Systematic Debugging

Random fixes waste time and create new bugs.

Core principle: ALWAYS find root cause before attempting fixes. Symptom fixes are failure.

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

Use ESPECIALLY when:

• Under time pressure (emergencies make guessing tempting)
• "Just one quick fix" seems obvious
• You've already tried multiple fixes
• 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

3. Check Recent Changes

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

4. Trace Data Flow Backward

   • Where does the bad value originate?
   • What called this with the bad value?
   • Keep tracing up until you find the source
   • Fix at source, not at symptom

5. Multi-Component Systems Add diagnostic instrumentation at each boundary:

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

Phase 2: Pattern Analysis

1. Find Working Examples - Similar working code in same codebase
2. Compare Against References - Read reference implementations completely
3. Identify Differences - List every difference, however small
4. Understand Dependencies - Settings, config, environment, 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 - Worked? Phase 4. Didn't work? New hypothesis.
4. When You Don't Know - Say so. Ask for help. Research more.

Phase 4: Implementation

1. Create Failing Test Case - Simplest possible reproduction
2. Implement Single Fix - ONE change at a time, no bundled improvements
3. Verify Fix - Test passes? No regressions?

If fix doesn't work:

• Count: How many fixes have you tried?
• If < 3: Return to Phase 1 with new information
• If >= 3: STOP and question the architecture

When 3+ Fixes Fail

Pattern indicating architectural problem:

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

STOP and question fundamentals:

• Is this pattern fundamentally sound?
• Should we refactor architecture vs. continue fixing symptoms?
• Discuss with user before attempting more fixes

Root Cause Tracing

When bugs manifest deep in the call stack:

1. Observe the Symptom - What error occurred?
2. Find Immediate Cause - What code directly causes this?
3. Ask: What Called This? - Trace up the call chain
4. Keep Tracing Up - What value was passed? Where did it come from?
5. Find Original Trigger - The source, not the symptom

Adding Stack Traces:

stack = capture_stack_trace()
log("DEBUG operation:", {
  input_value,
  current_directory,
  environment,
  stack
})

NEVER fix just where the error appears. Trace back to find the original trigger.

Red Flags - STOP and Follow Process

• "Quick fix for now, investigate later"
• "Just try changing X and see if it works"
• "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

Integration

Use with:

• code-test - Write failing test to reproduce bug before fixing
• completion-verify - Verify fix actually worked before claiming done

Reference

• defense-in-depth.md - Multi-layer validation patterns
• root-cause-tracing.md - Detailed tracing techniques