Edge Case Analysis: API Rate Limiting Feature

Current AC Coverage: 40% (basic functionality only, missing critical edge cases around boundaries, errors, concurrency, and user experience)

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Missing Edge Cases Identified (15 cases)

Category: Boundary Conditions

Edge Case 1: What happens at exactly 100 requests/minute? 🔴 CRITICAL PRIORITY
Current Status: Not defined
Suggested AC:

• “Request #100 within a minute is allowed and succeeds”
• “Request #101 within the same minute returns 429”
• “Counter resets precisely 60 seconds from the first request in the window”

Why Important: Off-by-one errors are extremely common; must clarify whether 100 is inclusive or exclusive

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Edge Case 2: What happens at request #99, #100, and #101? 🔴 HIGH PRIORITY
Current Status: Not defined
Suggested AC:

• “Request #99 succeeds with normal response”
• “Request #100 succeeds with normal response”
• “Request #101 returns 429 with rate limit headers”
• “All three scenarios are tested explicitly”

Why Important: Boundary testing prevents off-by-one bugs that commonly slip through

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Edge Case 3: What happens when user makes exactly 0 requests? 🟡 LOW PRIORITY
Current Status: Not defined
Suggested AC:

• “Users with 0 requests in current window can make requests normally”
• “Rate limit counter starts at 0 for new users”

Why Important: Edge case for new users or users during window reset

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Category: Empty/Null States

Edge Case 4: What if user identifier is missing or invalid? 🔴 CRITICAL PRIORITY
Current Status: Not defined (could allow unlimited requests)
Suggested AC:

• “Requests without valid user identifier return 401 Unauthorized”
• “Anonymous requests are not rate limited (or have separate limit if supported)”
• “Invalid user tokens are rejected before rate limiting check”

Why Important: Security risk - missing user ID could bypass rate limiting entirely

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Edge Case 5: What if user makes first API request ever? 🟡 MEDIUM PRIORITY
Current Status: Not defined
Suggested AC:

• “New user’s first request initializes rate limit counter”
• “First request is always allowed (counts as 1/100)”
• “Rate limit window starts from first request timestamp”

Why Important: Ensures smooth onboarding for new users

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Category: Error Scenarios

Edge Case 6: What if rate limit storage (Redis/DB) is unavailable? 🔴 CRITICAL PRIORITY
Current Status: Not defined (system could fail open or closed)
Suggested AC:

• “If rate limit storage is unavailable, fail closed (return 503 Service Unavailable)”
• “Include error message: ‘Service temporarily unavailable. Please try again.’”
• “Log storage failures for ops monitoring”
• “OR specify fail-open behavior with justification”

Why Important: Critical decision - determines whether system prioritizes availability or security during outages

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Edge Case 7: What if rate limit counter corruption occurs? 🔴 HIGH PRIORITY
Current Status: Not defined
Suggested AC:

• “If counter value is invalid/corrupted, reset to 0 and allow request”
• “Log corruption events for investigation”
• “System recovers gracefully without blocking users”

Why Important: Data corruption shouldn’t permanently block users

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Edge Case 8: What if system clock is adjusted (time goes backward)? 🟡 MEDIUM PRIORITY
Current Status: Not defined
Suggested AC:

• “Use monotonic clock for rate limit windows when available”
• “If time goes backward, maintain existing window or reset gracefully”
• “Document time synchronization requirements”

Why Important: Clock skew can cause unexpected rate limit behavior

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Category: Concurrent/Conflict Scenarios

Edge Case 9: What if requests #99, #100, and #101 arrive simultaneously? 🔴 CRITICAL PRIORITY
Current Status: Not defined (race condition risk)
Suggested AC:

• “Rate limit counter uses atomic increment operations”
• “Concurrent requests at the limit are handled consistently”
• “Maximum 1 request exceeds limit per concurrent batch (not multiple)”
• “Use distributed lock or atomic operations (Redis INCR, DB transactions)”

Why Important: Race conditions could allow users to exceed rate limit significantly

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Edge Case 10: What if multiple API nodes handle requests from same user? 🔴 HIGH PRIORITY
Current Status: Not defined (distributed system concern)
Suggested AC:

• “Rate limiting is enforced across all API nodes (centralized counter)”
• “Counter storage is shared (Redis, database, etc.)”
• “Counter updates are atomic and consistent”

Why Important: Distributed systems can leak rate limits without centralized enforcement

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Edge Case 11: What if user resets/changes their user ID? 🟡 MEDIUM PRIORITY
Current Status: Not defined
Suggested AC:

• “Each unique user ID has independent rate limit counter”
• “User ID changes result in new rate limit window”
• “Document user identifier used (API key, user ID, session ID, etc.)”

Why Important: Clarifies rate limiting scope and prevents abuse

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Category: Input Validation

Edge Case 12: What if request timestamp is in the future? 🟡 MEDIUM PRIORITY
Current Status: Not defined
Suggested AC:

• “Requests with future timestamps are treated as current time”
• “Reject requests with timestamps >5 minutes in future (clock skew tolerance)”

Why Important: Prevents time manipulation attacks

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Category: Network/Performance

Edge Case 13: What if 429 response delivery fails or is slow? 🟡 MEDIUM PRIORITY
Current Status: Not defined
Suggested AC:

• “429 responses are generated quickly (no expensive operations)”
• “Failed 429 delivery still counts against rate limit”
• “Rate limit headers are included even if response body fails”

Why Important: Rate limiting shouldn’t itself cause performance issues

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Category: User Experience

Edge Case 14: What information is included in 429 response? 🔴 HIGH PRIORITY
Current Status: Partially defined (429 mentioned, but not response details)
Suggested AC:

• “429 response includes Retry-After header with seconds until window reset”
• “Response includes X-RateLimit-Limit: 100 header”
• “Response includes X-RateLimit-Remaining header with requests left”
• “Response includes X-RateLimit-Reset header with reset timestamp”
• “Response body includes JSON: {'error': 'Rate limit exceeded', 'retry_after': <seconds>}”

Why Important: Standard rate limit headers allow clients to implement proper retry logic

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Edge Case 15: What happens when rate limit window resets? 🔴 HIGH PRIORITY
Current Status: Not defined (sliding window vs fixed window)
Suggested AC:

• “Specify window type: Fixed window (resets at 60-second intervals) OR Sliding window (per-user 60-second rolling window)”
• “Fixed window: All users’ counters reset at same intervals (e.g., top of each minute)”
• “Sliding window: Each user’s counter tracks last 60 seconds of requests”
• “Document choice and reasoning”

Why Important: Fundamentally different behaviors - sliding window is fairer but more complex

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Priority Summary

CRITICAL/HIGH (11 cases) - Must address:

• Boundary at exactly 100 requests (off-by-one errors)
• Requests #99, #100, #101 behavior
• Missing/invalid user identifier handling
• Storage unavailable failure mode (fail open vs fail closed)
• Counter corruption recovery
• Concurrent request race conditions
• Distributed system consistency
• 429 response headers and body format
• Rate limit window reset mechanism (fixed vs sliding)
• Rate limit headers on all responses
• Deleted counter corruption

MEDIUM (5 cases) - Should address:

• First request initialization
• System clock adjustment
• User ID changes
• Future timestamp handling
• Repeated 429 requests counting
• Internal/admin request handling

LOW (2 cases) - Nice to have:

• Zero requests edge case
• 429 response performance

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Coverage Improvement

Before: 2 acceptance criteria (basic happy path only)
After: 20 acceptance criteria (2 original + 18 edge cases)

Estimated Bugs Prevented: 12-15 (including critical race conditions, off-by-one errors, and security bypasses)

Recommended Next Steps:

1. URGENT: Review critical cases with engineering team (30-45 min):
   • Window reset strategy (fixed vs sliding) - architectural decision
   • Failure mode when storage unavailable (fail open vs fail closed)
   • Concurrent request handling strategy (atomic operations)
   • User identification method (API key, session, JWT)
2. Define 429 response format with standard rate limit headers
3. Add integration tests for boundary conditions (#99, #100, #101)
4. Add concurrent request tests (load testing)
5. Document rate limiting architecture for ops team (monitoring, troubleshooting)
6. Consider future: burst allowance, different limits per endpoint, premium user tiers