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Explain hash maps and solve array intersection

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a candidate's understanding of hash map internals — including array/bucket layout, hash function selection, collision resolution strategies, load factor and resizing behavior, deletion semantics, time-space trade-offs — alongside algorithmic problem-solving for computing intersections across k integer arrays and the generalization to elements appearing in at least t arrays, with attention to duplicates and edge cases. It is commonly asked to assess mastery of core data structures, algorithm design and complexity analysis within the Coding & Algorithms domain, testing both conceptual understanding of data-structure internals and practical application of algorithmic reasoning and performance trade-offs.

  • Medium
  • Citadel
  • Coding & Algorithms
  • Software Engineer

Explain hash maps and solve array intersection

Company: Citadel

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: Medium

Interview Round: Take-home Project

1) Explain the internal implementation of a hash map: underlying array/bucket layout, hash function choice, collision resolution strategies (separate chaining vs. open addressing), load factor thresholds and resizing/rehashing, deletion semantics, expected vs. worst-case time complexities, and typical memory trade-offs. 2) Given k integer arrays, return the sorted list of integers that appear in every array. Then extend your solution to return the integers that appear in at least t of the k arrays (1 ≤ t ≤ k). Provide algorithms, analyze time and space complexity, and discuss edge cases (e.g., duplicates within an array, empty arrays).

Quick Answer: This question evaluates a candidate's understanding of hash map internals — including array/bucket layout, hash function selection, collision resolution strategies, load factor and resizing behavior, deletion semantics, time-space trade-offs — alongside algorithmic problem-solving for computing intersections across k integer arrays and the generalization to elements appearing in at least t arrays, with attention to duplicates and edge cases. It is commonly asked to assess mastery of core data structures, algorithm design and complexity analysis within the Coding & Algorithms domain, testing both conceptual understanding of data-structure internals and practical application of algorithmic reasoning and performance trade-offs.

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Citadel
Jul 26, 2025, 12:00 AM
Software Engineer
Take-home Project
Coding & Algorithms
10
0
  1. Explain the internal implementation of a hash map: underlying array/bucket layout, hash function choice, collision resolution strategies (separate chaining vs. open addressing), load factor thresholds and resizing/rehashing, deletion semantics, expected vs. worst-case time complexities, and typical memory trade-offs.
  2. Given k integer arrays, return the sorted list of integers that appear in every array. Then extend your solution to return the integers that appear in at least t of the k arrays (1 ≤ t ≤ k). Provide algorithms, analyze time and space complexity, and discuss edge cases (e.g., duplicates within an array, empty arrays).

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