LinkedIn·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Jun 2026

Summary

LinkedIn SWE interview with a modified meeting scheduler design problem. Pretty focused on OOD and knowing your data structures cold, less hand-holdy than I expected.

Questions Asked (1)

Design a booking system with two functions: one to record a booking given a start and end time, and another to find the earliest available slot at or after a given start time that fits a requested duration without overlapping existing bookings. Define your data structures, handle edge cases, and walk through the complexity.

System DesignAlgorithms & Data StructuresData Modeling

Author's notes

I went straight to a sorted list of intervals and built from there.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then propose a data structure that supports efficient insertion and querying, such as a balanced binary search tree or sorted list of intervals. Walk through the algorithms for booking and finding the earliest available slot, analyze time and space complexity, and discuss edge cases like overlapping bookings and boundary conditions.

Pro tip: Demonstrate awareness of real-world constraints by discussing concurrency control and persistence, and mention how you would extend the design to support multiple resources or time zones.

1. Clarify Requirements and Assumptions

Ask questions to confirm whether bookings can overlap, if times are inclusive/exclusive, and if the system needs to handle concurrent requests. State any assumptions you make.

2. Choose Data Structures

Select a data structure that efficiently stores non-overlapping intervals and supports fast insertion and search, such as a balanced BST (e.g., TreeMap) or a sorted list with binary search.

3. Design Booking Function

Describe how to insert a new booking: validate no overlap, find the correct position, and update the data structure. Handle edge cases like adjacent bookings and invalid time ranges.

4. Design Earliest Available Slot Function

Explain how to find the earliest slot at or after a given start time that fits the duration: iterate through intervals, check gaps, and return the first valid slot or null if none exists.

5. Analyze Complexity and Edge Cases

State the time and space complexity for both operations, and discuss edge cases such as no bookings, booking at the very beginning/end, and overlapping requests.

Key Points to Mention

Use of a balanced binary search tree (e.g., TreeMap) or sorted list to maintain intervals sorted by start time.
Overlap detection: for a new booking [s, e), check if the previous interval's end > s or the next interval's start < e.
Earliest available slot algorithm: iterate through intervals, compute gaps, and check if gap length >= duration.
Time complexity: O(log n) for insertion and O(n) for finding a slot in the worst case, or O(log n) with augmented trees.
Edge cases: empty schedule, booking exactly adjacent to existing ones, requested duration longer than any gap, and invalid time ranges.
Concurrency and persistence considerations for a production system.

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