What is Interview Forge?

Interview Forge helps you practice mock interviews, follow study plans, track career goals, review learning analytics, and prepare across 36 pages.

LRU Cache at Apple — Interview Guide

How to approach LRU Cache in a Apple interview: the optimal approach, what Apple interviewers look for, and company-specific tips.

Updated 2026-09MediumDesign

The problem at Apple

Design a data structure that supports get(key) and put(key, value) in O(1) average time, with a fixed capacity that evicts the least-recently-used item when full.

Apple uses this problem to assess craft, detail, and domain depth. Expect Apple-specific follow-ups that tie the solution back to production reasoning and the company's engineering bar.

Key concepts

A hash map gives O(1) lookup by key.
A doubly linked list ordered by recency gives O(1) eviction and move-to-front.
Store list-node references in the map so you can detach a node without scanning.

Approach

On get: move the accessed node to the head (most recent); return its value.
On put: update if present (and move to head); otherwise insert at head and evict the tail if over capacity.
Use sentinel head/tail nodes to avoid null checks on detach.

Complexity

Operation	Time	Space
get	O(1)	O(capacity)
put	O(1)	O(capacity)

Unlock the full guide

Premium members get every DSA, system design, company and role interview guide — plus AI practice, mock interviews, and analytics.

Unlock with Premium