← Bloomberg Interview Insights

Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Bloomberg SWE interview with a classic data structures design problem. Pretty straightforward if you've seen it before, but there are enough moving parts to trip you up under pressure.

Questions Asked (1)

Q1

Design a data structure that supports insert, remove, and getRandom operations, all in average O(1) time. Insert should return false if the value already exists, remove should return false if the value is absent, and getRandom should return each element with equal probability.

Algorithms & Data StructuresSystem Design
Author's notes

The getRandom part is what makes this interesting.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Combine a dynamic array (for O(1) random access) with a hash map (for O(1) value-to-index lookup). For insert, append to the array and add to the map; for remove, swap the target with the last element, update the map, and pop; for getRandom, pick a random index from the array. This ensures average O(1) time for all operations.

Pro tip: Emphasize that the swap-with-last trick is the key to O(1) removal, and mention that you must update the hash map for the swapped element. Also, clarify that getRandom uses a uniform random index to guarantee equal probability.

1. Clarify requirements and constraints

Confirm that all operations must be average O(1), that insert/remove return booleans, and that getRandom must be uniform. Discuss edge cases like duplicates and empty structure.

2. Choose data structures

Select a dynamic array (list) for O(1) random access and a hash map for O(1) value-to-index mapping. Explain why each is needed.

3. Design insert operation

Check if value exists in map; if so, return false. Otherwise, append to array, record its index in map, and return true.

4. Design remove operation

Check if value exists in map; if not, return false. Swap the target element with the last element in the array, update the map for the swapped element, remove the last element, and delete the target from the map.

5. Design getRandom operation

Generate a random index uniformly from 0 to size-1, and return the element at that index in the array.

Key Points to Mention

  • Use a dynamic array (e.g., ArrayList in Java, list in Python) for O(1) random access.
  • Use a hash map (e.g., HashMap in Java, dict in Python) to store value-to-index mappings.
  • For removal, swap the element to remove with the last element, then pop the last element, updating the map for the swapped element.
  • Handle edge cases: removing the last element, removing when only one element exists, and ensuring map updates are consistent.
  • getRandom uses a uniform random number generator to pick an index, ensuring each element has equal probability.
  • All operations are average O(1) because hash map operations are O(1) on average and array operations (append, swap, pop) are O(1).

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