Google·Software Engineer·Onsite - Coding / Algorithms·Senior

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Jul 2026

Summary

Google SWE coding round, one problem the whole time. The question was LeetCode 2402 and they wanted more than just the heap solution.

Questions Asked (1)

You have n meeting rooms numbered 0 to n-1 and a list of meetings as half-open intervals. Rooms are assigned by specific rules around delays, smallest available room index, and reuse priority. Return the room that held the most meetings, breaking ties by smaller index.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Got the two-heap approach out pretty quickly, free rooms as a min-heap on index, occupied rooms as a min-heap on (end_time, room_index).

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AI HintsAI Generated

Suggested Approach

Clarify the exact room assignment rules (delay handling, smallest available index, reuse priority) and edge cases before designing. Then, propose an efficient algorithm using a min-heap for room availability and a counter for meetings per room, discussing time/space complexity and trade-offs.

Pro tip: Explicitly state your assumptions about the rules and confirm them with the interviewer; this shows attention to detail and avoids solving the wrong problem. Also, mention that you would test with edge cases like simultaneous meetings and zero meetings.

1. Clarify rules and constraints

Ask questions to pin down the exact assignment rules: how delays are handled, what 'smallest available room index' means, and the reuse priority. Also confirm input format, interval inclusivity, and constraints (e.g., n, number of meetings).

2. Design data structures

Choose a min-heap to track available room indices and another min-heap (or sorted structure) to track ongoing meetings by end time. Use an array to count meetings per room.

3. Simulate assignments

Process meetings in chronological order. For each meeting, free rooms whose meetings have ended, apply delay rules if any, assign the smallest available room, and update counters.

4. Compute result and analyze complexity

After processing all meetings, find the room with the maximum count, breaking ties by smaller index. State time complexity O(m log n) and space O(n + m).

5. Test and discuss trade-offs

Walk through edge cases (no meetings, all simultaneous, delays causing no available room). Discuss alternative approaches (e.g., sweep line) and trade-offs between simplicity and efficiency.

Key Points to Mention

Clarify the exact room assignment rules, especially delay handling and reuse priority.
Use a min-heap for available rooms to efficiently get the smallest index.
Track ongoing meetings with a min-heap keyed by end time to free rooms.
Maintain a count array for meetings per room and update it on each assignment.
Analyze time and space complexity: O(m log n) time, O(n + m) space.
Test edge cases: no meetings, all meetings simultaneous, delays causing no room available.

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