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The first three methods were fine, pretty much just bookkeeping with maps.
Start by clarifying the requirements and constraints, especially the timestamp semantics and ordering guarantee. Then design the data structures and algorithms, focusing on efficient user-task mappings and a priority queue for scheduled deletions. Finally, discuss trade-offs, edge cases, and potential concurrency issues.
Pro tip: Emphasize the importance of processing scheduled deletions before other operations at the same timestamp—this often requires a tie-breaking mechanism in your priority queue. Also, consider using a lazy deletion approach to avoid expensive removals from the task list.
Ask about the expected scale, timestamp granularity, and whether operations are synchronous or asynchronous. Confirm that scheduled deletions must be processed before any other operation at the same timestamp.
Choose appropriate structures: a map from user to set of tasks, a map from task to assigned user, and a priority queue (min-heap) for scheduled deletions keyed by timestamp with a tie-breaker to ensure deletions are processed first.
Implement addUser, assignTaskToUser, and unassignTaskToUser with O(1) average time using hash maps. For scheduleDeletion, add an entry to the priority queue with the deletion timestamp and a priority flag.
At each timestamp, process all scheduled deletions before any other operation. Use lazy deletion: when a deletion is due, check if the task still exists and is assigned to the same user before removing it.
Talk about time/space complexity, concurrency (if needed), and edge cases like deleting an already unassigned task or scheduling multiple deletions for the same task.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.