Meta·Software Engineer·Technical Phone Screen·Senior

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Jul 2026Remote

Summary

Meta data engineer phone screen, one algorithmic problem the whole time. Pretty focused session, they wanted code plus a real explanation of the sweep-line logic, not just a working solution.

Questions Asked (1)

Given a list of carpool trips where each trip has a passenger count, a start position, and an end position, implement a function that returns whether a vehicle with a fixed capacity can complete all trips without ever exceeding that capacity. The vehicle travels in one direction only. Aim for O(n log n) time and discuss what happens when multiple events fall on the same coordinate.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I went straight to the sweep-line idea, which felt right, +passengers at start and -passengers at end, sort all events, scan through.

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AI HintsAI Generated

Suggested Approach

Model each trip as two events: a pickup at the start location and a drop-off at the end location. Sort all events by location, and for events at the same location, process drop-offs before pickups to avoid false capacity violations. Then sweep through the sorted events, maintaining a running passenger count and checking against the capacity.

Pro tip: Explicitly discuss the tie-breaking rule for events at the same coordinate—processing drop-offs before pickups is crucial because a passenger getting off at a location frees capacity for another passenger getting on at the same location. This shows attention to edge cases and real-world correctness.

1. Clarify and Confirm

Restate the problem to ensure understanding: trips are one-directional, capacity is fixed, and we need to check if capacity is ever exceeded. Ask about constraints (e.g., number of trips, coordinate ranges) and confirm the tie-breaking rule for same-coordinate events.

2. Design the Event-Based Approach

Explain that each trip can be split into two events: a pickup (+passenger count) at the start and a drop-off (-passenger count) at the end. This transforms the problem into a sweep-line over sorted events.

3. Sort Events with Tie-Breaking

Sort events by location. For events at the same location, process drop-offs before pickups. This ensures that capacity is freed before new passengers board, preventing false positives.

4. Sweep and Validate Capacity

Iterate through sorted events, updating the current passenger count. After each event, check if the count exceeds capacity; if so, return false. If the sweep completes without violation, return true.

5. Analyze Complexity and Edge Cases

State that sorting takes O(n log n) time and O(n) space for events. Discuss edge cases: empty trips, zero capacity, trips with zero passengers, and multiple events at the same coordinate.

Key Points to Mention

Event-based sweep-line algorithm: split each trip into pickup and drop-off events.
Sorting events by location, with drop-offs before pickups at the same coordinate.
Maintain a running sum of passengers and compare to capacity after each event.
Time complexity O(n log n) due to sorting; space complexity O(n) for events.
Tie-breaking rule: process drop-offs first to avoid false capacity violations.
Edge cases: empty input, capacity zero, trips with zero passengers, and overlapping events at same location.

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