Apple·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate

May 2026

Summary

Apple SWE interview with a system design and OOD focus. The main problem was designing a deck of cards with shuffle and draw operations, which sounds almost too simple until you actually have to argue about probability guarantees and complexity out loud.

Questions Asked (1)

Design a deck of playing cards with Card, Deck, and supporting classes (like Suit and Rank enums). Implement shuffle() to produce a uniformly random permutation and draw() to remove and return a card while preserving uniform-random order. Discuss the correctness of the probability argument and the complexity of each operation.

System DesignAlgorithms & Data StructuresTechnical Trade-offs

Author's notes

I started with the class structure which was fine, Suit and Rank as enums, Card as a simple value object, Deck holding a list.

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AI HintsAI Generated

Suggested Approach

Start by outlining the class design with Card, Deck, Suit, and Rank, then implement shuffle using Fisher-Yates and draw by removing from the end. Explain the uniform random permutation proof and analyze time/space complexity for each operation.

Pro tip: Mention that using a list and swapping in-place avoids extra space, and that drawing from the end is O(1) while preserving uniformity. Also, discuss thread-safety if the deck is shared.

1. Class Design

Define Suit and Rank enums, and a Card class with suit and rank fields. Deck class holds a list of cards and supports shuffle and draw.

2. Shuffle Implementation

Implement Fisher-Yates shuffle: iterate from last index down to 1, swap each card with a randomly chosen card from the remaining unshuffled portion.

3. Draw Implementation

Implement draw by removing and returning the last card from the deck (or first if using a queue), ensuring O(1) time and preserving uniform random order.

4. Correctness Proof

Argue that each permutation is equally likely: at each step, the probability of any remaining card being placed at the current position is 1/(remaining count).

5. Complexity Analysis

Shuffle is O(n) time and O(1) extra space; draw is O(1) time. Discuss trade-offs if using other data structures.

Key Points to Mention

Fisher-Yates shuffle algorithm and its uniform random permutation property
In-place swapping to achieve O(1) extra space
Draw operation should be O(1) by removing from the end of the list
Proof of uniformity: each card has equal probability of ending up in any position
Time complexity: shuffle O(n), draw O(1); space complexity: O(n) for deck storage
Potential thread-safety considerations if deck is accessed concurrently

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