← Snapchat Interview Insights

Snapchat·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Snapchat software engineer interview that went deep into data structures fundamentals. The main ask was building a generic hash map from scratch in Swift, which sounds manageable until you're live-coding rehashing logic and justifying every design decision out loud.

Questions Asked (1)

Q1

Implement a generic Dictionary<Key: Hashable, Value> from scratch in Swift, without using the built-in Dictionary as backing storage. Your implementation should support subscript get/set, insertion, deletion, lookup, and iteration. Walk through your collision-resolution strategy, load factor choice, and resize/rehashing policy, and analyze the amortized time complexity of each operation.

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

I went with separate chaining because it felt safer to reason about under pressure, but the interviewer pushed back pretty hard asking why not open addressing, what the cache behavior difference is, and whether I'd change my answer for a memory-constrained environment.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by outlining the core components: an array of buckets, a hash function, and a collision resolution strategy. Then, implement the required operations with careful attention to resizing and load factor, and finally analyze the amortized time complexity of each operation.

Pro tip: Mention that you would use a prime number for the bucket count to reduce clustering, and discuss how Swift's built-in hashValue can be used but is not guaranteed stable across runs, so you might want to implement your own hash for consistency.

1. Define the data structure

Choose an array of buckets, where each bucket is a linked list (separate chaining) or use open addressing. Explain your choice and its implications.

2. Implement core operations

Write methods for subscript get/set, insert, delete, and lookup. Ensure they handle collisions and updates correctly.

3. Handle resizing and rehashing

Decide on a load factor threshold (e.g., 0.75) and describe how to resize the bucket array and rehash all existing keys when the threshold is exceeded.

4. Implement iteration

Provide a way to iterate over all key-value pairs, such as by conforming to Sequence and implementing a custom iterator that traverses buckets.

5. Analyze complexity

Discuss the average and worst-case time complexities for each operation, emphasizing amortized O(1) for insertions and deletions due to resizing.

Key Points to Mention

  • Collision resolution strategy: separate chaining vs. open addressing (linear probing, quadratic probing, double hashing) and trade-offs.
  • Load factor choice: typical values (0.75) and how it affects performance and memory.
  • Resize policy: when to resize (e.g., when load factor exceeds threshold), how to resize (double the capacity), and rehashing all elements.
  • Amortized time complexity: O(1) average for insert, delete, lookup; O(n) worst-case; amortized O(1) for resizing.
  • Hash function: using Swift's Hashable protocol, potential issues with hash flooding, and mitigation strategies.
  • Iteration: implementing Sequence protocol, handling mutations during iteration, and order guarantees (none).

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