Transform debugging from frustrating guesswork into systematic problem-solving with proven strategies, powerful tools, and methodical approaches. - Tracking down elusive bugs - Investigating performance issues
## 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
// 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
# 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
## 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`); } });
## 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
## 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)