LRU Cache

CodingAnthropicLast reported July 2026High Frequency
Reported
12× across candidate reports
First seen
June 2025
Last reported
July 2026
Also asked in
Phone Screen, OA
Reported outcome
mixed

Problem Overview

You are given a Python LRU cache implementation (skeleton or partially complete code) that acts like a memoization decorator, similar to Python's functools.lru_cache. The cache is backed by an OrderedDict (capacity, eviction, move_to_end logic may already be provided). The problem has multiple parts: Part 1 – Bug Fix / Key…

  • 6 candidate-reported follow-ups — the exact probes interviewers asked, with the trigger for each
  • The rest of the problem statement — full requirements, constraints, and edge cases
  • Approach and trade-offs — what passing candidates did, and the mistakes that sink people
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Verified Source
Every question is reconstructed from multiple independent candidate reports. Verbatim follow-ups, not invented ones.
Codex Fact-Checked
Technical claims, formulas, and scale numbers are reviewed against primary sources.
Interviewer Follow-ups
The exact follow-ups reported by candidates, with the trigger that prompts each one — plus the mistakes that sink people.
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