home / skills / yanko-belov / code-craft / race-conditions

race-conditions skill

/skills/race-conditions

This skill helps you identify and remediate race conditions by applying atomic, transactional, and locking patterns across code paths.

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---
name: race-conditions
description: Use when multiple operations access shared state. Use when order of operations matters. Use when "it works most of the time" but occasionally fails mysteriously.
---

# Race Conditions

## Overview

**When outcome depends on timing, you have a race. Races are bugs waiting to happen.**

Race conditions occur when correctness depends on the relative timing of events. They're insidious because they work most of the time, fail randomly, and are nearly impossible to reproduce.

## When to Use

- Multiple async operations access shared state
- Database read-then-write patterns
- Concurrent API requests modify same resource
- "Works in development, fails in production"
- Intermittent bugs that can't be reproduced

## The Iron Rule

```
NEVER read-then-write without atomicity guarantees.
```

**No exceptions:**
- Not for "it's fast, timing won't matter"
- Not for "only one user at a time"
- Not for "we'll fix it if it breaks"
- Not for "it works in testing"

**If timing can affect outcome, you have a race condition.**

## Detection: The TOCTOU Pattern

Time-Of-Check to Time-Of-Use: checking something, then acting on it.

```typescript
// ❌ VIOLATION: Classic race condition
async function withdrawMoney(accountId: string, amount: number): Promise<void> {
  // Time-of-check
  const account = await db.accounts.findById(accountId);
  if (account.balance >= amount) {
    // Time-of-use (gap where another transaction can happen!)
    await db.accounts.update(accountId, {
      balance: account.balance - amount  // Uses stale value!
    });
  }
}

// Two simultaneous $80 withdrawals from $100 account:
// T1: Reads balance = $100 ✓
// T2: Reads balance = $100 ✓  (race!)
// T1: balance >= 80? Yes. Update to $20
// T2: balance >= 80? Yes. Update to $20  (should have been denied!)
// Result: Two $80 withdrawals, final balance $20 (should be overdraft error)
```

## Correct Patterns

### 1. Atomic Operations

```typescript
// ✅ CORRECT: Atomic update with condition
async function withdrawMoney(accountId: string, amount: number): Promise<boolean> {
  const result = await db.accounts.updateOne(
    { 
      _id: accountId,
      balance: { $gte: amount }  // Check AND update atomically
    },
    { 
      $inc: { balance: -amount } 
    }
  );
  
  if (result.modifiedCount === 0) {
    throw new InsufficientFundsError(accountId, amount);
  }
  
  return true;
}
```

### 2. Database Transactions

```typescript
// ✅ CORRECT: Transaction with proper isolation
async function transferMoney(
  fromId: string, 
  toId: string, 
  amount: number
): Promise<void> {
  await db.transaction(async (tx) => {
    // Lock rows with FOR UPDATE
    const from = await tx.accounts
      .findById(fromId)
      .forUpdate();  // Locks row until commit
    
    const to = await tx.accounts
      .findById(toId)
      .forUpdate();
    
    if (from.balance < amount) {
      throw new InsufficientFundsError(fromId, amount);
    }
    
    await tx.accounts.update(fromId, { balance: from.balance - amount });
    await tx.accounts.update(toId, { balance: to.balance + amount });
    
    // Commit releases locks
  });
}
```

### 3. Optimistic Locking

```typescript
// ✅ CORRECT: Optimistic locking with version
async function updateDocument(
  id: string, 
  updates: Partial<Document>
): Promise<Document> {
  const maxRetries = 3;
  
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    const doc = await db.documents.findById(id);
    
    const result = await db.documents.updateOne(
      { 
        _id: id,
        version: doc.version  // Only update if version matches
      },
      { 
        $set: updates,
        $inc: { version: 1 }  // Increment version
      }
    );
    
    if (result.modifiedCount > 0) {
      return { ...doc, ...updates, version: doc.version + 1 };
    }
    
    // Version mismatch - someone else updated, retry
    await sleep(Math.random() * 100);  // Jitter
  }
  
  throw new ConcurrentModificationError(id);
}
```

### 4. Distributed Locks

```typescript
// ✅ CORRECT: Distributed lock for complex operations
async function processOrder(orderId: string): Promise<void> {
  const lockKey = `order:${orderId}:lock`;
  const lockTTL = 30000; // 30 seconds
  
  const lock = await redis.acquireLock(lockKey, lockTTL);
  if (!lock) {
    throw new OrderAlreadyProcessingError(orderId);
  }
  
  try {
    // Safe - only one process can be here for this order
    await doExpensiveOrderProcessing(orderId);
  } finally {
    await redis.releaseLock(lockKey, lock);
  }
}
```

### 5. Idempotency Keys

```typescript
// ✅ CORRECT: Idempotency prevents duplicate processing
async function createPayment(
  idempotencyKey: string,
  data: PaymentData
): Promise<Payment> {
  // Check if already processed
  const existing = await db.payments.findByIdempotencyKey(idempotencyKey);
  if (existing) {
    return existing;  // Return previous result
  }
  
  // Try to claim the idempotency key atomically
  try {
    await db.idempotencyKeys.insert({
      key: idempotencyKey,
      status: 'processing',
      createdAt: new Date(),
    });
  } catch (error) {
    if (isDuplicateKeyError(error)) {
      // Another request claimed it - fetch and return
      const existing = await db.payments.findByIdempotencyKey(idempotencyKey);
      if (existing) return existing;
      throw new PaymentProcessingError('Payment in progress');
    }
    throw error;
  }
  
  // Safe to process - we own the idempotency key
  const payment = await processPayment(data);
  
  await db.idempotencyKeys.update(idempotencyKey, {
    status: 'completed',
    result: payment.id,
  });
  
  return payment;
}
```

## Common Race Condition Patterns

| Pattern | Problem | Solution |
|---------|---------|----------|
| Check-then-act | State changes between check and act | Atomic check-and-act |
| Read-modify-write | Value changes after read | Atomic update or lock |
| Lazy initialization | Multiple threads initialize | Double-checked locking or atomic init |
| Counter increment | Lost updates | Atomic increment |
| First-one-wins | Multiple claim "first" | Atomic claim with unique constraint |

## Language-Specific Patterns

### JavaScript/Node.js

```typescript
// ❌ VIOLATION: Shared state in closure
let requestCount = 0;
async function handleRequest() {
  requestCount++;  // Race! Read-modify-write is NOT atomic
  // ...
}

// ✅ CORRECT: Atomic counter
import { createClient } from 'redis';
const redis = createClient();

async function handleRequest() {
  const count = await redis.incr('request_count');  // Atomic
  // ...
}
```

### Python

```python
# ❌ VIOLATION: Check-then-act
def get_or_create(key: str, factory: Callable) -> Any:
    if key not in cache:  # Check
        cache[key] = factory()  # Act - race!
    return cache[key]

# ✅ CORRECT: Atomic with lock
from threading import Lock
lock = Lock()

def get_or_create(key: str, factory: Callable) -> Any:
    with lock:
        if key not in cache:
            cache[key] = factory()
        return cache[key]
```

## Pressure Resistance Protocol

### 1. "It's Fast, Timing Won't Matter"
**Pressure:** "The operation takes microseconds"

**Response:** Production load creates overlap. Under load, "fast" operations overlap frequently. Race conditions scale with traffic.

**Action:** Use atomic operations. Speed doesn't prevent races.

### 2. "Only One User at a Time"
**Pressure:** "Low traffic, won't have concurrent requests"

**Response:** Users double-click. Tabs refresh. Bots hammer. Mobile retries on timeout. "Low traffic" has bursts.

**Action:** Design for concurrency even if you don't expect it.

### 3. "We'll Fix It If It Breaks"
**Pressure:** "Ship now, fix later"

**Response:** Race conditions are nearly impossible to reproduce. You'll spend weeks debugging "random" failures.

**Action:** Build it correctly now. Cheaper than debugging later.

### 4. "It Works in Testing"
**Pressure:** "All tests pass"

**Response:** Tests run sequentially. Production runs concurrently. Race conditions hide in serial execution.

**Action:** Write concurrent tests. Load test. Assume races exist.

## Red Flags - STOP and Reconsider

If you notice ANY of these patterns, you likely have a race:

- `if (condition) { update based on condition }`
- `read(); compute(); write(computed);`
- `check availability; book;`
- `get count; increment; save count;`
- Global or shared mutable state
- "Works most of the time"
- "Can't reproduce in development"
- Timeouts that "fix" intermittent bugs

**All of these mean: Add atomicity guarantees.**

## Testing for Race Conditions

```typescript
// Concurrent test to expose races
describe('withdraw', () => {
  it('handles concurrent withdrawals correctly', async () => {
    await db.accounts.create({ id: 'test', balance: 100 });
    
    // Simulate 10 concurrent $20 withdrawals
    const withdrawals = Array(10).fill(null).map(() => 
      withdrawMoney('test', 20).catch(() => 'failed')
    );
    
    const results = await Promise.all(withdrawals);
    const successful = results.filter(r => r !== 'failed').length;
    
    // Only 5 should succeed (5 × $20 = $100)
    expect(successful).toBe(5);
    
    const account = await db.accounts.findById('test');
    expect(account.balance).toBe(0);
  });
});
```

## Common Rationalizations (All Invalid)

| Excuse | Reality |
|--------|---------|
| "It's fast enough" | Fast operations still overlap under load. |
| "Low traffic" | Retries, double-clicks, bots create concurrency. |
| "Works in dev" | Dev is serial. Prod is parallel. |
| "Fix when it breaks" | Race bugs are unfindable. Fix now. |
| "Just add a sleep" | Sleeps don't fix races, just hide them. |
| "Users won't do that" | Users do everything you don't expect. |

## Quick Reference

| Scenario | Solution |
|----------|----------|
| Balance check before update | Atomic conditional update |
| Increment counter | Atomic increment (Redis INCR, SQL += 1) |
| Complex multi-step operation | Database transaction with locks |
| Cross-service operation | Distributed lock |
| Duplicate request prevention | Idempotency key |
| Version conflicts | Optimistic locking |

## The Bottom Line

**If correctness depends on timing, you have a bug.**

Read-then-write is a race. Check-then-act is a race. Any gap between observing state and acting on it is a race. Use atomic operations, transactions, locks, or idempotency keys. Never assume "it's fast enough" or "traffic is low."

Overview

This skill helps you find and fix race conditions where correctness depends on timing between operations. It targets code that “works most of the time” but fails intermittently when multiple actors access or mutate shared state. Use its patterns to replace fragile check-then-act sequences with atomic operations, transactions, locks, or idempotency.

How this skill works

The skill inspects code paths that read state and later write based on that read (TOCTOU), shared mutable variables, and patterns like read-modify-write or lazy initialization. It suggests concrete remedies: atomic database updates, transactions with row locks, optimistic locking with version checks, distributed locks, and idempotency keys. It also provides test patterns to reproduce concurrency failures.

When to use it

  • Multiple async operations access shared state
  • Database read-then-write workflows
  • Concurrent API requests that modify the same resource
  • Intermittent, non-deterministic failures in production
  • When order of operations matters or “it usually works” excuses appear

Best practices

  • Never perform read-then-write without atomicity guarantees
  • Prefer database atomic ops or transactions for state changes spanning multiple steps
  • Use optimistic locking with version checks and retries where locking is too costly
  • Adopt idempotency keys for repeatable external-facing operations
  • Use distributed locks for complex multi-service workflows
  • Write concurrent tests and load tests to expose timing bugs

Example use cases

  • Account withdrawals: replace read-then-update with atomic conditional update or transaction
  • Payment processing: claim an idempotency key atomically to prevent duplicates
  • Order processing: acquire a distributed lock per order to ensure single-worker processing
  • Counters and quotas: use atomic increments (Redis INCR, SQL atomic ops) instead of read/increment/write
  • Document updates in high-concurrency apps: use optimistic locking with version field and retry

FAQ

How do I know if I actually have a race?

Look for check-then-act code, shared mutable state, lost updates, or bugs that only appear under load. If correctness depends on timing, treat it as a race until proven otherwise.

When should I use optimistic locking instead of a lock or transaction?

Use optimistic locking when conflicts are rare and you want higher concurrency. Use transactions or locks when operations must serialize or when side effects make retries unsafe.