My first instinct was a plain array and i was halfway through coding it before realizing delete anywhere in the queue kills you.
Start by clarifying requirements and constraints, then propose a data structure that balances time complexity for each operation. Discuss trade-offs between different approaches (e.g., linked list vs. balanced BST vs. segment tree) and justify your final design. Finally, outline the implementation details and analyze time/space complexity.
Pro tip: Emphasize that find_first_match is a read-only operation and should not modify the waitlist, which is a common pitfall. Also, mention that you would consider concurrency and scalability if this were a real system.
Ask about expected number of users, frequency of operations, and whether party sizes are bounded. Confirm that find_first_match should not remove the user and that ties are broken by join time.
Suggest a few candidate structures: a simple linked list with linear scan, a balanced BST keyed by join time with additional indexing by party size, or a segment tree over party sizes storing earliest join time. Discuss pros and cons.
Choose one approach (e.g., segment tree) and explain why it meets the requirements efficiently. For example, segment tree can support O(log N) find_first_match by querying the range [table_size, max_party_size] for the minimum join time.
Describe how to implement join, delete, and find_first_match. For segment tree, explain how to update the tree on join/delete and how to query for the earliest join time in a range.
State time and space complexity for each operation. For segment tree: O(log N) for all operations, O(N) space. Compare with alternatives like O(1) join but O(N) find_first_match.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.