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debugging-strategies

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Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.

General

What this skill does


# Debugging Strategies

Transform debugging from frustrating guesswork into systematic problem-solving with proven strategies, powerful tools, and methodical approaches.

## When to Use This Skill

- Tracking down elusive bugs
- Investigating performance issues
- Understanding unfamiliar codebases
- Debugging production issues
- Analyzing crash dumps and stack traces
- Profiling application performance
- Investigating memory leaks
- Debugging distributed systems

## Core Principles

### 1. The Scientific Method

**1. Observe**: What's the actual behavior?
**2. Hypothesize**: What could be causing it?
**3. Experiment**: Test your hypothesis
**4. Analyze**: Did it prove/disprove your theory?
**5. Repeat**: Until you find the root cause

### 2. Debugging Mindset

**Don't Assume:**
- "It can't be X" - Yes it can
- "I didn't change Y" - Check anyway
- "It works on my machine" - Find out why

**Do:**
- Reproduce consistently
- Isolate the problem
- Keep detailed notes
- Question everything
- Take breaks when stuck

### 3. Rubber Duck Debugging

Explain your code and problem out loud (to a rubber duck, colleague, or yourself). Often reveals the issue.

## Systematic Debugging Process

### Phase 1: Reproduce

```markdown
## Reproduction Checklist

1. **Can you reproduce it?**
   - Always? Sometimes? Randomly?
   - Specific conditions needed?
   - Can others reproduce it?

2. **Create minimal reproduction**
   - Simplify to smallest example
   - Remove unrelated code
   - Isolate the problem

3. **Document steps**
   - Write down exact steps
   - Note environment details
   - Capture error messages
```

### Phase 2: Gather Information

```markdown
## Information Collection

1. **Error Messages**
   - Full stack trace
   - Error codes
   - Console/log output

2. **Environment**
   - OS version
   - Language/runtime version
   - Dependencies versions
   - Environment variables

3. **Recent Changes**
   - Git history
   - Deployment timeline
   - Configuration changes

4. **Scope**
   - Affects all users or specific ones?
   - All browsers or specific ones?
   - Production only or also dev?
```

### Phase 3: Form Hypothesis

```markdown
## Hypothesis Formation

Based on gathered info, ask:

1. **What changed?**
   - Recent code changes
   - Dependency updates
   - Infrastructure changes

2. **What's different?**
   - Working vs broken environment
   - Working vs broken user
   - Before vs after

3. **Where could this fail?**
   - Input validation
   - Business logic
   - Data layer
   - External services
```

### Phase 4: Test & Verify

```markdown
## Testing Strategies

1. **Binary Search**
   - Comment out half the code
   - Narrow down problematic section
   - Repeat until found

2. **Add Logging**
   - Strategic console.log/print
   - Track variable values
   - Trace execution flow

3. **Isolate Components**
   - Test each piece separately
   - Mock dependencies
   - Remove complexity

4. **Compare Working vs Broken**
   - Diff configurations
   - Diff environments
   - Diff data
```

## Debugging Tools

### JavaScript/TypeScript Debugging

```typescript
// Chrome DevTools Debugger
function processOrder(order: Order) {
    debugger;  // Execution pauses here

    const total = calculateTotal(order);
    console.log('Total:', total);

    // Conditional breakpoint
    if (order.items.length > 10) {
        debugger;  // Only breaks if condition true
    }

    return total;
}

// Console debugging techniques
console.log('Value:', value);                    // Basic
console.table(arrayOfObjects);                   // Table format
console.time('operation'); /* code */ console.timeEnd('operation');  // Timing
console.trace();                                 // Stack trace
console.assert(value > 0, 'Value must be positive');  // Assertion

// Performance profiling
performance.mark('start-operation');
// ... operation code
performance.mark('end-operation');
performance.measure('operation', 'start-operation', 'end-operation');
console.log(performance.getEntriesByType('measure'));
```

**VS Code Debugger Configuration:**
```json
// .vscode/launch.json
{
    "version": "0.2.0",
    "configurations": [
        {
            "type": "node",
            "request": "launch",
            "name": "Debug Program",
            "program": "${workspaceFolder}/src/index.ts",
            "preLaunchTask": "tsc: build - tsconfig.json",
            "outFiles": ["${workspaceFolder}/dist/**/*.js"],
            "skipFiles": ["<node_internals>/**"]
        },
        {
            "type": "node",
            "request": "launch",
            "name": "Debug Tests",
            "program": "${workspaceFolder}/node_modules/jest/bin/jest",
            "args": ["--runInBand", "--no-cache"],
            "console": "integratedTerminal"
        }
    ]
}
```

### Python Debugging

```python
# Built-in debugger (pdb)
import pdb

def calculate_total(items):
    total = 0
    pdb.set_trace()  # Debugger starts here

    for item in items:
        total += item.price * item.quantity

    return total

# Breakpoint (Python 3.7+)
def process_order(order):
    breakpoint()  # More convenient than pdb.set_trace()
    # ... code

# Post-mortem debugging
try:
    risky_operation()
except Exception:
    import pdb
    pdb.post_mortem()  # Debug at exception point

# IPython debugging (ipdb)
from ipdb import set_trace
set_trace()  # Better interface than pdb

# Logging for debugging
import logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

def fetch_user(user_id):
    logger.debug(f'Fetching user: {user_id}')
    user = db.query(User).get(user_id)
    logger.debug(f'Found user: {user}')
    return user

# Profile performance
import cProfile
import pstats

cProfile.run('slow_function()', 'profile_stats')
stats = pstats.Stats('profile_stats')
stats.sort_stats('cumulative')
stats.print_stats(10)  # Top 10 slowest
```

### Go Debugging

```go
// Delve debugger
// Install: go install github.com/go-delve/delve/cmd/dlv@latest
// Run: dlv debug main.go

import (
    "fmt"
    "runtime"
    "runtime/debug"
)

// Print stack trace
func debugStack() {
    debug.PrintStack()
}

// Panic recovery with debugging
func processRequest() {
    defer func() {
        if r := recover(); r != nil {
            fmt.Println("Panic:", r)
            debug.PrintStack()
        }
    }()

    // ... code that might panic
}

// Memory profiling
import _ "net/http/pprof"
// Visit http://localhost:6060/debug/pprof/

// CPU profiling
import (
    "os"
    "runtime/pprof"
)

f, _ := os.Create("cpu.prof")
pprof.StartCPUProfile(f)
defer pprof.StopCPUProfile()
// ... code to profile
```

## Advanced Debugging Techniques

### Technique 1: Binary Search Debugging

```bash
# Git bisect for finding regression
git bisect start
git bisect bad                    # Current commit is bad
git bisect good v1.0.0            # v1.0.0 was good

# Git checks out middle commit
# Test it, then:
git bisect good   # if it works
git bisect bad    # if it's broken

# Continue until bug found
git bisect reset  # when done
```

### Technique 2: Differential Debugging

Compare working vs broken:

```markdown
## What's Different?

| Aspect       | Working         | Broken          |
|--------------|-----------------|-----------------|
| Environment  | Development     | Production      |
| Node version | 18.16.0         | 18.15.0         |
| Data         | Empty DB        | 1M records      |
| User         | Admin           | Regular user    |
| Browser      | Chrome          | Safari          |
| Time         | During day      | After midnight  |

Hypothesis: Time-based issue? Check timezone handling.
```

### Technique 3: Trace Debugging

```typescript
// Function call tracing
function trace(target: any, propertyKey: string, descriptor: PropertyDescriptor) {
    const originalMethod = descriptor.value;

    descriptor.value = function(...args: any[]) {
        console.log(`Calling ${propertyKey} with args:`, args);
        co

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