The subset checking part is straightforward enough but the naive approach gets slow fast when the lists are long.
Convert each person's favorite companies list into a set for O(1) lookups, then for each person check if their set is a subset of any other person's set. If not, include their index; finally sort the indices in increasing order.
Pro tip: Mention that you can optimize by first sorting people by list size descending and only checking against larger sets, or by using bitsets if company IDs are small. This shows awareness of performance trade-offs.
Confirm that 'subset' means every company in person A's list is also in person B's list, and that a person's list is not a subset of itself. Ask about input size and constraints.
Convert each person's list of favorite companies into a hash set to allow O(1) membership checks and efficient subset operations.
For each person i, iterate over all other persons j and check if set_i is a subset of set_j. If any such j exists, person i is excluded.
Add indices of people whose set is not a subset of any other to a result list, then sort the list in increasing order before returning.
Discuss time complexity O(n^2 * k) where k is average list size, and mention possible optimizations like sorting by size or using bitsets.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.