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Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Bloomberg coding round, one design question the whole time. Pretty focused session, they wanted both the concept and a working implementation before the clock ran out.

Questions Asked (1)

Q1

Design and implement a data structure that supports adding a participant, removing a participant, and picking a uniformly random participant, with all three operations running in O(1) average time.

Algorithms & Data StructuresSystem Design
Author's notes

I knew the hash map piece pretty fast but kept second-guessing the array side.

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AI HintsAI Generated

Suggested Approach

Use a combination of a dynamic array (list) and a hash map (dictionary) to achieve O(1) average time for all operations. The array stores the participants, and the hash map maps each participant to its index in the array. For removal, swap the element to be removed with the last element, update the hash map, and then remove the last element. For random selection, simply pick a random index in the array.

Pro tip: Discuss edge cases such as removing the last element, handling duplicates, and the importance of maintaining the hash map correctly during swaps. Also, mention that this design is similar to the 'Insert Delete GetRandom O(1)' problem on LeetCode, which is a common interview question.

1. Clarify requirements and constraints

Ask if participants are unique, if duplicates are allowed, and if the random selection needs to be uniformly distributed. Confirm that all operations must be O(1) average time.

2. Choose data structures

Select a dynamic array to store participants for O(1) random access and a hash map to store participant-to-index mappings for O(1) lookup and removal.

3. Design add operation

Append the new participant to the array and add its index to the hash map. If duplicates are not allowed, check the hash map first.

4. Design remove operation

Look up the participant's index in the hash map. Swap the participant with the last element in the array, update the hash map for the swapped element, then remove the last element from the array and the participant from the hash map.

5. Design random pick operation

Generate a random index between 0 and the array size minus 1, and return the participant at that index. This ensures uniform random selection.

Key Points to Mention

  • Use of a dynamic array (e.g., ArrayList in Java, list in Python) for O(1) random access.
  • Use of a hash map (e.g., HashMap in Java, dict in Python) for O(1) average-time insert, delete, and lookup.
  • Swap-with-last technique for O(1) removal from the array.
  • Handling of edge cases: removing the last element, removing the only element, and updating the hash map correctly during swaps.
  • Uniform random selection by picking a random index from the array.
  • Time complexity analysis: all operations are O(1) on average, with O(n) space complexity.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.