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

IntermediatePrefer not to say

Jun 2026

Summary

Google SWE coding round with one simulation problem that looks manageable until you realize the assignment policy has to be exact or your example output is just wrong.

Questions Asked (1)

Given a list of car rental bookings (each a half-open interval [start, end)), assign bookings to the minimum number of cars using a specific deterministic policy: sort bookings by start, then end, then original index; always assign to the lowest-numbered free car; spin up a new car only when none are free. Return the car number that handled the most bookings, with ties broken by smallest car number.

Algorithms & Data Structures

Author's notes

The interval scheduling part felt familiar but the strict assignment policy is where I got tripped up.

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AI HintsAI Generated

Suggested Approach

Clarify the deterministic policy and edge cases, then outline an efficient algorithm using sorting and a min-heap of free car numbers. Simulate the assignment process while tracking booking counts per car, and finally return the car with the most bookings (smallest index on tie).

Pro tip: Mention that the half-open interval [start, end) means a car is free at the exact end time, so when processing bookings sorted by start, you must release cars whose end <= current start. Also, emphasize that the deterministic tie-breaking (start, end, index) ensures consistent output, which is crucial for testing.

1. Clarify requirements and edge cases

Confirm the sorting criteria, tie-breaking rules, and interval semantics (half-open). Discuss edge cases like empty input, simultaneous start/end, and multiple bookings with identical start and end.

2. Design the algorithm

Sort bookings by (start, end, original index). Use a min-heap to track free car numbers and a min-heap (or sorted structure) to track busy cars by end time. Simulate assignments, releasing cars when their end <= current start.

3. Simulate and track counts

Iterate through sorted bookings: release all cars with end <= current start, assign the lowest-numbered free car (or create a new one if none free), and increment that car's booking count. Record the car's end time in the busy heap.

4. Determine the result

After processing all bookings, find the car with the maximum booking count. If multiple cars tie, return the smallest car number.

5. Analyze complexity and test

State time complexity O(n log n) due to sorting and heap operations, and space O(n). Walk through a small example to verify correctness, including tie-breaking.

Key Points to Mention

Sorting criteria: start, then end, then original index to ensure deterministic order.
Half-open interval [start, end): car is free at end time, so release condition is end <= current start.
Use a min-heap for free car numbers to always pick the lowest-numbered available car.
Use a min-heap (or priority queue) for busy cars keyed by end time to efficiently release cars.
Track booking counts per car in an array or hash map, updating on each assignment.
Tie-breaking: when multiple cars have the same max bookings, return the smallest car number.
Time complexity: O(n log n) due to sorting and heap operations; space O(n).

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