debugging

Find root cause before fixing. Symptom fixes are failure.

Iron Law: NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

When to Use

Answer IN ORDER. Stop at first match:

1. Bug, error, or test failure? → Use this skill
2. Unexpected behavior? → Use this skill
3. Previous fix didn't work? → Use this skill (especially important)
4. Performance problem? → Use this skill
5. None of above? → Skip this skill

Use especially when:

• Under time pressure (emergencies make guessing tempting)
• "Quick fix" seems obvious (red flag)
• Already tried 1+ fixes that didn't work

The Four Phases

Complete each phase before proceeding.

Phase 1: Root Cause Investigation

BEFORE attempting ANY fix:

1. Read Error Messages Completely

Don't skip past errors. They often contain the exact solution.
- Full stack trace (note line numbers, file paths)
- Error codes and messages
- Warnings that preceded the error

2. Reproduce Consistently

| Can reproduce? | Action | | --------------- | ---------------------------------------------------- | | Yes, every time | Proceed to step 3 | | Sometimes | Gather more data - when does it happen vs not? | | Never | Cannot debug what you cannot reproduce - gather logs |

3. Check Recent Changes

git diff HEAD~5          # Recent code changes
git log --oneline -10    # Recent commits

What changed that could cause this? Dependencies? Config? Environment?

4. Trace Data Flow (Root Cause Tracing)

When error is deep in call stack:

Symptom: Error at line 50 in utils.js
    ↑ Called by handler.js:120
    ↑ Called by router.js:45
    ↑ Called by app.js:10 ← ROOT CAUSE: bad input here

Technique:

1. Find where error occurs (symptom)
2. Ask: "What called this with bad data?"
3. Trace up until you find the SOURCE
4. Fix at source, not at symptom

5. Multi-Component Systems

When system has multiple layers (API → service → database):

# Log at EACH boundary before proposing fixes
echo "=== Layer 1 (API): request=$REQUEST ==="
echo "=== Layer 2 (Service): input=$INPUT ==="
echo "=== Layer 3 (DB): query=$QUERY ==="

Run once to find WHERE it breaks. Then investigate that layer.

Phase 2: Pattern Analysis

1. Find Working Examples

Locate similar working code in same codebase. What works that's similar?

2. Identify Differences

| Working code | Broken code | Could this matter? | | ---------------- | -------------- | ------------------ | | Uses async/await | Uses callbacks | Yes - timing | | Validates input | No validation | Yes - bad data |

List ALL differences. Don't assume "that can't matter."

Phase 3: Hypothesis Testing

1. Form Single Hypothesis

Write it down: "I think X is the root cause because Y"

Be specific:

• ❌ "Something's wrong with the database"
• ✅ "Connection pool exhausted because connections aren't released in error path"

2. Test Minimally

| Rule | Why | | ------------------------ | ---------------------- | | ONE change at a time | Isolate what works | | Smallest possible change | Avoid side effects | | Don't bundle fixes | Can't tell what helped |

3. Evaluate Result

| Result | Action | | --------------- | --------------------------------------- | | Fixed | Phase 4 (verify) | | Not fixed | NEW hypothesis (return to 3.1) | | Partially fixed | Found one issue, continue investigating |

Phase 4: Implementation

1. Create Failing Test

Before fixing, write test that fails due to the bug:

it('handles empty input without crashing', () => {
  // This test should FAIL before fix, PASS after
  expect(() => processData('')).not.toThrow();
});

2. Implement Fix

• Address ROOT CAUSE identified in Phase 1
• ONE change
• No "while I'm here" improvements

3. Verify

• [ ] New test passes
• [ ] Existing tests still pass
• [ ] Issue actually resolved (not just test passing)

4. If Fix Doesn't Work

| Fix attempts | Action | | ------------ | ---------------------------------------- | | 1-2 | Return to Phase 1 with new information | | 3+ | STOP - Question architecture (see below) |

5. After 3+ Failed Fixes: Question Architecture

Pattern indicating architectural problem:

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

STOP and ask:

• Is this pattern fundamentally sound?
• Should we refactor vs. continue patching?
• Discuss with user before more fix attempts

Red Flags - STOP Immediately

If you catch yourself thinking:

| Thought | Reality | | ---------------------------------------------- | --------------------------------- | | "Quick fix for now, investigate later" | Investigate NOW or you never will | | "Just try changing X" | That's guessing, not debugging | | "I'll add multiple fixes and test" | Can't isolate what worked | | "I don't fully understand but this might work" | You need to understand first | | "One more fix attempt" (after 2+ failures) | 3+ failures = wrong approach |

ALL mean: STOP. Return to Phase 1.

Quick Reference

| Phase | Key Question | Success Criteria | | ----------------- | ------------------------------------- | ---------------------------------- | | 1. Root Cause | "WHY is this happening?" | Understand cause, not just symptom | | 2. Pattern | "What's different from working code?" | Identified key differences | | 3. Hypothesis | "Is my theory correct?" | Confirmed or formed new theory | | 4. Implementation | "Does the fix work?" | Test passes, issue resolved |