Question Bank
Hash Table Basics Quiz
Difficulty: Easy
Short prompts on hash table lookup cost, collision handling, and when to reach for a Set vs a Map. Builds the mental model before harder hashing problems.
Hash Table Basics Quiz
Short prompts on hash table lookup cost, collision handling, and when to reach for a Set vs a Map. Builds the mental model before harder hashing problems.
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13
Trace this snippet and explain what each line prints. Which of the two structures is right for counting frequencies, and which for membership testing?
Examples
Example 1:
Input: iterate 'banana' building seen (Set) and counts (Map); then print seen.size, counts.get('a'), counts.has('z')
Output: 3, then 3, then false
Explanation: Sets dedupe so seen ends as {b, a, n} (size 3). Map stores per-key totals, so counts.get('a') is 3. 'z' was never inserted, so counts.has('z') is false. Use Set for membership, Map for per-key payload.Implement firstUnique(arr) returning the first element that appears exactly once in arr, or null if none exists. Aim for O(n) time using a hash structure.
Examples
Example 1:
Input: arr = ['a', 'b', 'c', 'a', 'b']
Output: 'c'
Explanation: Counts are {a: 2, b: 2, c: 1}. Walking the original array, 'a' and 'b' have count 2 and are skipped; 'c' has count 1 and is returned.Example 2:
Input: arr = ['x', 'x', 'y', 'y']
Output: null
Explanation: Every element repeats, so no key has count 1 and the function returns null.Two distinct keys hash to the same bucket index. What happens in a hash table that uses separate chaining versus one that uses open addressing (linear probing)? Which is more cache-friendly?