Cursor·Backend Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Cursor backend interview, one coding round, one problem the whole time. The question looks clean on paper but there are enough edge cases to keep you busy for a while.

Questions Asked (1)

Implement a rate limiter function that takes a user ID and a timestamp and returns whether the notification attempt should be allowed. The system enforces sliding-window limits over the past 10 minutes at three levels simultaneously: per user (max 3), per team (max 10), and per company (max 20). Allowed requests must be recorded immediately; denied ones must not. Timestamps are integers in seconds and arrive in non-decreasing order. Be ready to walk through test cases and discuss complexity.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I went straight to a deque-per-entity approach, one deque each for user, team, and company, and prune entries older than 600 seconds before checking counts.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements and assumptions, then design a solution using a sliding window log with deques for each level (user, team, company). Explain how to check all three limits atomically and only record the timestamp if all pass, then discuss complexity and test cases.

Pro tip: Emphasize that the non-decreasing timestamps allow efficient pruning of expired entries, and that atomicity across the three levels is crucial to avoid partial updates. Also, mention that using a single timestamp for all levels ensures consistency.

1. Clarify Requirements and Assumptions

Ask about the mapping of user to team and company, whether the rate limiter is per user or global, and if timestamps are guaranteed non-decreasing. Confirm that limits are inclusive (e.g., max 3 means the 4th within 10 minutes is denied).

2. Design Data Structures

Use a hash map to map user ID to team ID and company ID. For each user, team, and company, maintain a deque (or queue) of timestamps of allowed requests within the last 10 minutes. Since timestamps are non-decreasing, we can prune from the front when the oldest timestamp is <= current_timestamp - 600.

3. Implement the Rate Limiter Logic

On each request, first prune expired timestamps from all relevant deques (user, team, company). Then check if adding the current timestamp would exceed any limit. If all pass, append the timestamp to all three deques and return true; otherwise, return false without modifying any deque.

4. Analyze Complexity and Edge Cases

Time complexity: O(1) amortized per request because each timestamp is added and removed at most once per level. Space complexity: O(U + T + C) where U, T, C are the number of users, teams, and companies with recent activity. Discuss edge cases: exactly at limit, timestamp exactly 10 minutes old, multiple users in same team/company, and non-decreasing timestamps.

5. Walk Through Test Cases

Provide concrete examples: e.g., user A makes 3 requests at t=0,1,2; 4th at t=3 should be denied. At t=601, a new request should be allowed because the first expired. Also test team and company limits with multiple users. Show how the deques are updated.

Key Points to Mention

Sliding window log approach with deques for efficient pruning.
Atomic check-and-update: only record if all three limits pass.
Leverage non-decreasing timestamps to prune expired entries in O(1) amortized time.
Time and space complexity analysis.
Handling of edge cases: exact boundary conditions, multiple users in same team/company.
Potential optimizations: using a single timestamp list per entity, or combining limits if hierarchy is fixed.

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