Design a Phone Directory (Set/Trie)
Design a phone directory that allows users to check if a number exists, reserve a number, and release a number. Optimize for checking and reserving.
Why Interviewers Ask This
Stripe evaluates this question to assess a candidate's ability to balance space-time trade-offs in real-world resource management. They specifically look for how you optimize frequent read operations against dynamic allocation patterns, testing your grasp of hash sets versus tries and your capacity to design systems that handle high-throughput number reservation without collisions.
How to Answer This Question
1. Clarify requirements immediately: define the scope of 'phone numbers' (fixed length vs variable) and whether the directory needs to support prefix searches or just exact matches. 2. Propose an initial naive solution using a simple array or list, then explicitly critique its O(n) lookup time as insufficient for Stripe's scale. 3. Introduce the optimal data structure: recommend a HashSet for O(1) average case lookups if exact matching is all that is needed, or a Trie if prefix validation is required. 4. Discuss edge cases like range limits, duplicate reservations, and concurrent access if the system scales. 5. Walk through the code logic for reserve and release operations, emphasizing constant time complexity for both adding and removing entries to ensure the system remains responsive under load.
Key Points to Cover
- Explicitly choosing between HashSet and Trie based on specific constraints
- Demonstrating awareness of O(1) time complexity for critical operations
- Addressing concurrency and race conditions typical of Stripe's environment
- Discussing space efficiency when dealing with large ranges of numbers
- Validating input formats to prevent invalid number entry
Sample Answer
To design this phone directory efficiently, I first clarify that we need O(1) performance for checking existence and reserving numbers, as Stripe values low-latency APIs. A simple array would require linear scanning, whi…
Common Mistakes to Avoid
- Ignoring the difference between exact match and prefix search needs
- Forgetting to handle the scenario where a number is released and re-allocated
- Overlooking potential integer overflow issues when treating numbers as primitives
- Failing to discuss thread safety in a high-concurrency distributed system context
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