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Sig·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

SIG software engineer interview with a classic systems design problem dressed up as a coding question. The movie theatre seat booking problem sounds almost trivial until you're actually in it and realize how many design decisions stack up fast.

Questions Asked (1)

Q1

Design and implement a movie theatre seat booking system that supports booking a group of adjacent seats, cancelling bookings, and optionally handling a middle aisle that splits each row into two segments. Discuss your data structures, time complexity, and how you'd handle concurrency at scale.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

I started with a naive per-row array scan and the interviewer immediately pushed on what happens with a 10,000-seat venue under heavy load.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements (e.g., seat layout, middle aisle, concurrency needs) and then propose a data structure like a segment tree or bitset to efficiently find and book adjacent seats. Discuss trade-offs between simplicity and performance, and outline a concurrency strategy such as optimistic locking or partitioning.

Pro tip: Demonstrate awareness of real-world constraints: mention that in high-concurrency scenarios, you might need to handle race conditions with distributed locks or transactional isolation, and that the choice of data structure depends on read/write patterns.

1. Clarify Requirements

Ask about seat layout (rows, columns, middle aisle), booking constraints (group size, adjacency), and expected scale (concurrent users, number of seats).

2. Design Data Structures

Propose a data structure to represent seat availability, such as a bitset per row or a segment tree, and explain how to efficiently find adjacent seats.

3. Implement Core Operations

Describe algorithms for booking (find and reserve adjacent seats), cancelling (free seats), and handling the middle aisle by splitting rows into segments.

4. Analyze Complexity

Discuss time and space complexity for each operation, comparing alternatives (e.g., linear scan vs. segment tree) and justifying your choice.

5. Address Concurrency

Explain how to handle concurrent bookings at scale, using techniques like optimistic locking, partitioning by row, or distributed transactions, and discuss trade-offs.

Key Points to Mention

  • Use of bitsets or segment trees for efficient seat availability queries
  • Handling middle aisle by treating each row as two independent segments
  • Time complexity: O(log n) for segment tree vs. O(n) for linear scan
  • Concurrency control: optimistic locking with versioning or pessimistic locking
  • Partitioning strategy to reduce contention (e.g., by row or theatre section)
  • Trade-offs between consistency and availability in distributed systems

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