My first instinct was a hashmap from username to login count, which covers the counting part fine.
Clarify the requirements and constraints, then propose a solution using a hash map to track login counts and a queue or linked list to maintain the order of single-visit users. Discuss time and space complexity, and consider edge cases and potential optimizations.
Pro tip: Demonstrate awareness of real-world concerns like concurrency and scalability, and mention how you would handle them in a production environment.
Ask questions to confirm details: What defines a 'login event'? Should the earliest single-visit user be based on the time of their first login? Are usernames unique? What are the expected scale and performance requirements?
Choose a hash map to store each user's login count and a queue (or doubly linked list) to maintain the order of users who have logged in exactly once. The queue allows O(1) retrieval of the earliest single-visit user.
For recordLogin(username): increment the user's count in the hash map. If the count becomes 1, add the username to the queue. If it becomes 2, remove the username from the queue (if present). For getEarliestSingleVisitUser(): remove and return the front of the queue if it still has count 1, otherwise dequeue and continue until a valid user is found or the queue is empty.
Explain that both operations are O(1) amortized time: recordLogin does constant work, and getEarliestSingleVisitUser may dequeue multiple stale entries but each user is dequeued at most once. Space complexity is O(n) for n unique users.
Cover scenarios like no single-visit users, users with multiple logins, and concurrent access. Mention potential extensions such as handling timestamps or distributed systems.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.