| name | debugging-strategies |
| description | 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. |
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
## 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
## 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
## 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
## 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
// 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:
// .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
# 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
// 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
# 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:
## 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
// Function call tracing
function trace(target: any, propertyKey: string, descriptor: PropertyDescriptor) {
const originalMethod = descriptor.value;
descriptor.value = function(...args: any[]) {
console.log(`Calling ${propertyKey} with args:`, args);
const result = originalMethod.apply(this, args);
console.log(`${propertyKey} returned:`, result);
return result;
};
return descriptor;
}
class OrderService {
@trace
calculateTotal(items: Item[]): number {
return items.reduce((sum, item) => sum + item.price, 0);
}
}
Technique 4: Memory Leak Detection
// Chrome DevTools Memory Profiler
// 1. Take heap snapshot
// 2. Perform action
// 3. Take another snapshot
// 4. Compare snapshots
// Node.js memory debugging
if (process.memoryUsage().heapUsed > 500 * 1024 * 1024) {
console.warn('High memory usage:', process.memoryUsage());
// Generate heap dump
require('v8').writeHeapSnapshot();
}
// Find memory leaks in tests
let beforeMemory: number;
beforeEach(() => {
beforeMemory = process.memoryUsage().heapUsed;
});
afterEach(() => {
const afterMemory = process.memoryUsage().heapUsed;
const diff = afterMemory - beforeMemory;
if (diff > 10 * 1024 * 1024) { // 10MB threshold
console.warn(`Possible memory leak: ${diff / 1024 / 1024}MB`);
}
});
Debugging Patterns by Issue Type
Pattern 1: Intermittent Bugs
## Strategies for Flaky Bugs
1. **Add extensive logging**
- Log timing information
- Log all state transitions
- Log external interactions
2. **Look for race conditions**
- Concurrent access to shared state
- Async operations completing out of order
- Missing synchronization
3. **Check timing dependencies**
- setTimeout/setInterval
- Promise resolution order
- Animation frame timing
4. **Stress test**
- Run many times
- Vary timing
- Simulate load
Pattern 2: Performance Issues
## Performance Debugging
1. **Profile first**
- Don't optimize blindly
- Measure before and after
- Find bottlenecks
2. **Common culprits**
- N+1 queries
- Unnecessary re-renders
- Large data processing
- Synchronous I/O
3. **Tools**
- Browser DevTools Performance tab
- Lighthouse
- Python: cProfile, line_profiler
- Node: clinic.js, 0x
Pattern 3: Production Bugs
## Production Debugging
1. **Gather evidence**
- Error tracking (Sentry, Bugsnag)
- Application logs
- User reports
- Metrics/monitoring
2. **Reproduce locally**
- Use production data (anonymized)
- Match environment
- Follow exact steps
3. **Safe investigation**
- Don't change production
- Use feature flags
- Add monitoring/logging
- Test fixes in staging
Best Practices
- Reproduce First: Can't fix what you can't reproduce
- Isolate the Problem: Remove complexity until minimal case
- Read Error Messages: They're usually helpful
- Check Recent Changes: Most bugs are recent
- Use Version Control: Git bisect, blame, history
- Take Breaks: Fresh eyes see better
- Document Findings: Help future you
- Fix Root Cause: Not just symptoms
Common Debugging Mistakes
- Making Multiple Changes: Change one thing at a time
- Not Reading Error Messages: Read the full stack trace
- Assuming It's Complex: Often it's simple
- Debug Logging in Prod: Remove before shipping
- Not Using Debugger: console.log isn't always best
- Giving Up Too Soon: Persistence pays off
- Not Testing the Fix: Verify it actually works
Quick Debugging Checklist
## When Stuck, Check:
- [ ] Spelling errors (typos in variable names)
- [ ] Case sensitivity (fileName vs filename)
- [ ] Null/undefined values
- [ ] Array index off-by-one
- [ ] Async timing (race conditions)
- [ ] Scope issues (closure, hoisting)
- [ ] Type mismatches
- [ ] Missing dependencies
- [ ] Environment variables
- [ ] File paths (absolute vs relative)
- [ ] Cache issues (clear cache)
- [ ] Stale data (refresh database)
Resources
- references/debugging-tools-guide.md: Comprehensive tool documentation
- references/performance-profiling.md: Performance debugging guide
- references/production-debugging.md: Debugging live systems
- assets/debugging-checklist.md: Quick reference checklist
- assets/common-bugs.md: Common bug patterns
- scripts/debug-helper.ts: Debugging utility functions