debugging-patterns skill

---
name: debugging-patterns
description: "Internal skill. Use cc10x-router for all development tasks."
allowed-tools: Read, Grep, Glob, Bash
---

# 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.

## Quick Five-Step Process (Reference Pattern)

For rapid debugging, use this concise flow:

```
1. Capture error message and stack trace
2. Identify reproduction steps
3. Isolate the failure location
4. Implement minimal fix
5. Verify solution works
```

**Debugging techniques:**
- Analyze error messages and logs
- Check recent code changes
- Form and test hypotheses
- **Add strategic debug logging**
- **Inspect variable states**

**Root Cause Tracing Technique:**
```
1. Observe symptom - Where does error manifest?
2. Find immediate cause - Which code produces the error?
3. Ask "What called this?" - Map call chain upward
4. Keep tracing up - Follow invalid data backward
5. Find original trigger - Where did problem actually start?
```
**Never fix solely where errors appear—trace to the original trigger.**

**For each issue provide:**
- Root cause explanation
- Evidence supporting diagnosis
- Specific code fix
- Testing approach
- Prevention recommendations

## Common Debugging Scenarios

### Test Failures
```
1. Read FULL error message and stack trace
2. Identify which assertion failed and why
3. Check test setup - is environment correct?
4. Check test data - are mocks/fixtures correct?
5. Trace to source of unexpected value
```

### Runtime Errors
```
1. Capture full stack trace
2. Identify line that throws
3. Check what values are undefined/null
4. Trace backward to where bad value originated
5. Add validation at the source
```

### "It worked before"
```
1. Use `git bisect` to find breaking commit
2. Compare change with previous working version
3. Identify what assumption changed
4. Fix at source of assumption violation
```

### Intermittent Failures
```
1. Look for race conditions
2. Check for shared mutable state
3. Examine async operation ordering
4. Look for timing dependencies
5. Add deterministic waits or proper synchronization
```

## 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)
- Manager wants it fixed NOW (systematic is faster than thrashing)

## 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 (CI → build → signing, API → service → database):**

   **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
   ```

   **Example (multi-layer system):**
   ```bash
   # Layer 1: Entry point
   echo "=== Input data: ==="
   echo "Request: ${REQUEST}"

   # Layer 2: Processing layer
   echo "=== After processing: ==="
   echo "Transformed: ${TRANSFORMED}"

   # Layer 3: Output layer
   echo "=== Final state: ==="
   echo "Result: ${RESULT}"
   ```

   **This reveals:** Which layer fails (input → processing ✓, processing → output ✗)

5. **Trace Data Flow**

   **WHEN error is deep in call stack:**
   - 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
   - What works that's similar to what's broken?

2. **Compare Against References**
   - If implementing pattern, read reference implementation COMPLETELY
   - Don't skim - read every line
   - Understand the pattern fully before applying

3. **Identify Differences**
   - What's different between working and broken?
   - List every difference, however small
   - Don't assume "that can't matter"

4. **Understand Dependencies**
   - What other components does this need?
   - What settings, config, environment?
   - What assumptions does it make?

### Phase 3: Hypothesis and Testing

**Scientific method:**

1. **Form Single Hypothesis**
   - State clearly: "I think X is the root cause because Y"
   - Write it down
   - Be specific, not vague

2. **Test Minimally**
   - Make the SMALLEST possible change to test hypothesis
   - One variable at a time
   - Don't fix multiple things at once

3. **Verify Before Continuing**
   - Did it work? Yes → Phase 4
   - Didn't work? Form NEW hypothesis
   - DON'T add more fixes on top

4. **When You Don't Know**
   - Say "I don't understand X"
   - Don't pretend to know
   - Ask for help
   - Research more

### Hypothesis Quality Criteria

**Falsifiability Requirement:** A good hypothesis can be proven wrong. If you can't design an experiment to disprove it, it's not useful.

**Bad (unfalsifiable):**
- "Something is wrong with the state"
- "The timing is off"
- "There's a race condition somewhere"

**Good (falsifiable):**
- "User state resets because component remounts when route changes"
- "API call completes after unmount, causing state update on unmounted component"
- "Two async operations modify same array without locking, causing data loss"

**The difference:** Specificity. Good hypotheses make specific, testable claims.

### Cognitive Biases in Debugging

| Bias | Trap | Antidote |
|------|------|----------|
| **Confirmation** | Only look for evidence supporting your hypothesis | "What would prove me wrong?" |
| **Anchoring** | First explanation becomes your anchor | Generate 3+ hypotheses before investigating any |
| **Availability** | Recent bugs → assume similar cause | Treat each bug as novel until evidence suggests otherwise |
| **Sunk Cost** | Spent 2 hours on path, keep going despite evidence | Every 30 min: "If fresh, would I take this path?" |

### Phase 4: Implementation

**Fix the root cause, not the symptom:**

1. **Create Failing Test Case**
   - Simplest possible reproduction
   - Automated test if possible
   - One-off test script if no framework
   - MUST have before fixing

2. **Implement Single Fix**
   - Address the root cause identified
   - ONE change at a time
   - No "while I'm here" improvements
   - No bundled refactoring

3. **Verify Fix**
   - Test passes now?
   - No other tests broken?
   - Issue actually resolved?

4. **If Fix Doesn't Work**
   - STOP
   - Count: How many fixes have you tried?
   - If < 3: Return to Phase 1, re-analyze with new information
   - **If >= 3: STOP and question the architecture (step 5 below)**
   - DON'T attempt Fix #4 without architectural discussion

5. **If 3+ Fixes Failed: Question Architecture**

   **Pattern indicating architectural problem:**
   - Each fix reveals new shared state/coupling/problem in different place
   - Fixes require "massive refactoring" to implement
   - Each fix creates new symptoms elsewhere

   **STOP and question fundamentals:**
   - Is this pattern fundamentally sound?
   - Are we "sticking with it through sheer inertia"?
   - Should we refactor architecture vs. continue fixing symptoms?

   **Discuss with your human partner before attempting more fixes**

   This is NOT a failed hypothesis - this is a wrong architecture.

## 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"
- "Pattern says X but I'll adapt it differently"
- "Here are the main problems: [lists fixes without investigation]"
- Proposing solutions before tracing data flow
- **"One more fix attempt" (when already tried 2+)**
- **Each fix reveals new problem in different place**

**ALL of these mean: STOP. Return to Phase 1.**

**If 3+ fixes failed:** Question the architecture (see Phase 4.5)

## User's Signals You're Doing It Wrong

**Watch for these redirections:**
- "Is that not happening?" - You assumed without verifying
- "Will it show us...?" - You should have added evidence gathering
- "Stop guessing" - You're proposing fixes without understanding
- "Ultrathink this" - Question fundamentals, not just symptoms
- "We're stuck?" (frustrated) - Your approach isn't working

**When you see these:** STOP. Return to Phase 1.

## Rationalization Prevention

| 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. |
| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |

## 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 |

## When Process Reveals "No Root Cause"

If systematic investigation reveals issue is truly environmental, timing-dependent, or external:

1. You've completed the process
2. Document what you investigated
3. Implement appropriate handling (retry, timeout, error message)
4. Add monitoring/logging for future investigation

**But:** 95% of "no root cause" cases are incomplete investigation.

## Output Format

```markdown
## Bug Investigation

### Phase 1: Evidence Gathered
- **Error**: [exact error message]
- **Stack trace**: [relevant lines]
- **Reproduction**: [steps to reproduce]
- **Recent changes**: [commits/changes]

### Phase 2: Pattern Analysis
- **Working example**: [similar working code]
- **Key differences**: [what's different]

### Phase 3: Hypothesis
- **Theory**: [I think X because Y]
- **Test**: [minimal change made]
- **Result**: [confirmed/refuted]

### Phase 4: Fix
- **Root cause**: [actual cause with evidence]
- **Change**: [summary of fix]
- **File**: [path:line]
- **Regression test**: [test added]

### Verification
- Test command: [command] → exit 0
- All tests: PASS
- Functionality: Restored
```

## Real-World Impact

From debugging sessions:
- Systematic approach: 15-30 minutes to fix
- Random fixes approach: 2-3 hours of thrashing
- First-time fix rate: 95% vs 40%
- New bugs introduced: Near zero vs common