Clarify the requirements and constraints, then propose a design using a doubly linked list to maintain the order of users who have logged in exactly once, combined with a hash map for O(1) access to each user's node and login count. Explain how recording a login updates the count and moves the user in or out of the list, ensuring both operations remain O(1).
Pro tip: Mention edge cases like duplicate logins and users who log in again after being in the once-list, and discuss how to handle them without breaking O(1) operations. Also, briefly compare with alternative approaches (e.g., two hash maps) to show depth.
Ask about the definition of 'earliest' (e.g., first login time or insertion order), whether user IDs are bounded, and if the stream is infinite. Confirm that both operations must be strictly O(1) time.
Propose a doubly linked list to maintain the order of users with exactly one login, and a hash map from user ID to a node containing login count and a pointer to the list node. This allows O(1) updates and access.
For recordLogin(userId): increment the user's login count. If it becomes 1, append the user to the end of the list. If it becomes 2, remove the user's node from the list. For getEarliestOnce(): return the head of the list if non-empty, else null.
Discuss what happens when a user logs in more than twice (count >2), when the list is empty, and when a user who was removed logs in again (count becomes 3, no list change). Ensure no duplicate entries in the list.
Confirm that both operations are O(1) time and O(n) space, where n is the number of distinct users. Mention that the linked list operations (append, remove) are O(1) given direct node access.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.