The insert and getRandom parts clicked fast for me.
Start by clarifying the requirements: average O(1) for insert, remove, and getRandom, and whether duplicates are allowed. Then propose a hybrid data structure: an array (or dynamic array) for O(1) random access and a hash map for O(1) lookup of element indices. Explain how to maintain consistency between them during insert and remove, using swap-with-last for O(1) removal.
Pro tip: Mention that getRandom relies on uniform random index selection from the array, and that the hash map stores indices to enable O(1) removal. Also note that if duplicates are allowed, the hash map can store a set of indices per value, but removal becomes more complex; clarifying this upfront shows thoroughness.
Ask whether duplicates are allowed, whether the data structure needs to support other operations, and confirm that average O(1) is acceptable (not worst-case).
Use a dynamic array (list) to store elements for O(1) random access, and a hash map to map each element to its index in the array for O(1) lookup.
Append the new element to the array and record its index in the hash map. Both operations are O(1) on average.
To remove an element, look up its index in the hash map. Swap it with the last element in the array, update the hash map for the swapped element, then remove the last element from the array and delete the entry from the hash map. This achieves O(1) average time.
getRandom simply picks a random index from the array and returns the element, which is O(1). Overall, all operations are O(1) average time, and space is O(n) for n elements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.