Microsoft·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Microsoft coding round, got a rate limiter problem that seemed manageable at first but the boundary condition stuff took longer than I expected. Left feeling okay but not great about it.

Questions Asked (1)

Build a sliding window rate limiter with an allow(client_id, timestamp) function that enforces a max of N requests per W-second window. Include test cases for boundary conditions.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I started with a fixed window approach and they let me finish before pointing out it doesn't actually solve the sliding part.

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Suggested Approach

Start by clarifying requirements (e.g., strict vs. approximate, memory constraints, concurrency) and then design a data structure that efficiently tracks request timestamps per client. Implement the allow function using a deque or circular buffer to maintain the sliding window, and thoroughly test boundary conditions like exactly N requests, window edges, and timestamp ordering.

Pro tip: Discuss trade-offs between strict and approximate sliding windows (e.g., using a ring buffer of counters) and mention how to handle out-of-order timestamps or clock skew, as these are common in real systems.

1. Clarify Requirements

Ask about expected request rates, memory limits, whether timestamps are monotonic, and if the limiter should be distributed. This ensures you design the right solution.

2. Choose Data Structures

Select a per-client data structure (e.g., deque, circular buffer, or timestamp queue) to store request timestamps within the window. Consider memory and time complexity.

3. Implement allow Function

On each call, remove timestamps older than timestamp - W, check if the count is less than N, and if so, add the current timestamp and return true; otherwise return false.

4. Handle Edge Cases and Concurrency

Address boundary conditions (exactly N requests, window edges), out-of-order timestamps, and thread safety if needed. Discuss cleanup of stale client data.

5. Design Test Cases

Write tests for: first N requests allowed, N+1th denied, requests exactly at window boundary, timestamps out of order, and multiple clients. Include stress tests for performance.

Key Points to Mention

Time and space complexity: O(1) amortized per request with deque, O(N) space per client.
Trade-offs between strict sliding window and approximate methods (e.g., fixed window counters, sliding window log).
Handling of out-of-order timestamps: either reject or sort, and implications.
Memory management: eviction of old timestamps and cleanup of inactive clients.
Concurrency: locking per client or using thread-safe data structures.
Boundary conditions: exactly N requests, requests at t and t+W, and timestamp equal to window edge.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.