Explain hash maps and solve array intersection

Q: Explain hash maps and solve array intersection

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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Question

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.
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).

Explain hash maps and solve array intersection

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