Start by clarifying requirements: what operations are needed (lock, unlock, is_available), expected scale, and concurrency needs. Then propose a design using a hash map from account_id to a min-heap of lock expiration timestamps, allowing efficient lazy deletion of expired locks. For is_available, check if the account has any active lock at time t by peeking the heap and removing expired locks.
Pro tip: Mention that you would use a min-heap per account to store lock expiration times, enabling O(log n) lock insertion and O(1) availability check after lazy cleanup. Also discuss how to handle concurrent access with fine-grained locking or lock-free structures if needed.
Ask about expected number of accounts, lock/unlock frequency, concurrency requirements, and whether locks can be extended or removed early.
Propose a hash map from account_id to a min-heap of lock expiration timestamps. Explain why a heap is efficient for tracking the earliest expiration.
Define lock(account_id, t) to push t onto the heap, and is_available(account_id, t) to lazily remove expired locks (those <= t) and then check if any lock remains.
State time complexities: O(log n) for lock, amortized O(log n) for is_available due to lazy deletion. Discuss potential optimizations like using a balanced BST or a sorted list if locks are few.
Discuss thread-safety using locks or concurrent data structures. Handle edge cases: no locks, multiple locks, locks in the past, and time precision.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
The max() formula tripped me up for a second.
First, clarify the requirements and edge cases, then implement the method using a hash map to store locked_until times. Explain the formula and discuss potential concurrency issues and trade-offs.
Pro tip: Mention that the formula effectively extends the lock from the later of the current time and the existing lock, which prevents race conditions and ensures monotonic locking.
Ask about the data type of t and duration, whether account_id is guaranteed to exist, and if thread safety is required.
Use a hash map (dictionary) to map account_id to locked_until timestamp. Consider if additional metadata is needed.
Compute new_locked_until = max(existing_locked_until, t) + duration and update the map. Handle missing account_id by treating existing as 0 or -infinity.
Discuss O(1) time and space per operation, and trade-offs like memory usage vs. speed, and concurrency handling.
Consider cases where t is in the past, duration is zero, or multiple acquires overlap. Verify the formula's behavior.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the requirements and constraints, then design a data structure that efficiently tracks the least recently used (LRU) available account. Implement the auto_acquire method using a combination of a hash map and a doubly linked list to achieve O(1) operations, and discuss trade-offs such as concurrency and persistence.
Pro tip: Emphasize the importance of handling edge cases like no available accounts and ensuring thread safety, as Stripe values robust and scalable solutions. Also, mention that you would write unit tests to verify the LRU behavior, especially for accounts never previously acquired.
Ask questions to confirm assumptions: Is the method expected to be thread-safe? What should happen if no accounts are available? Should the method block or return an error? How is 'duration' used—does it set a lock timeout?
Select a hash map for O(1) account lookup and a doubly linked list to maintain the LRU order. Accounts never acquired are placed at the tail (oldest) initially.
On acquire, remove the least recently used available account from the list, mark it as locked, and move it to the most recently used position. On release, move it back to the available list at the most recent position.
Use locks or concurrent data structures to ensure thread safety. Handle cases like no available accounts by throwing an exception or returning null, and consider lock expiration based on duration.
Talk about time/space complexity, potential bottlenecks, and how the design would scale. Mention alternatives like using a priority queue with timestamps if duration-based expiration is needed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.