Start by clarifying the problem scope and requirements with the interviewer, then propose a high-level design that addresses core functionality. Iterate on the design by diving into scalability, trade-offs, and bottlenecks, and conclude by summarizing how the design meets the requirements.
Pro tip: Always quantify your design decisions with back-of-the-envelope calculations to demonstrate data-driven reasoning. Also, proactively discuss potential failure modes and how to mitigate them, showing you think about reliability from the start.
Ask questions to understand functional and non-functional requirements, such as expected scale, latency, consistency, and availability needs. This ensures you design the right system.
Sketch the main components (e.g., clients, load balancers, services, databases, caches) and how they interact. Focus on the core user flows and data flow.
Choose critical components (e.g., data storage, messaging, sharding) and discuss their design in detail, including technology choices and trade-offs.
Explain how the system scales horizontally, handles bottlenecks (e.g., via caching, partitioning, replication), and meets performance goals.
Summarize key trade-offs made (e.g., consistency vs. availability) and how they align with requirements. Mention potential improvements or future work.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the modifications to the standard LRU cache, then outline your design using a hash map and doubly linked list. Explain how the doubly linked list enables O(1) operations and justify why it's optimal for this use case.
Pro tip: Mention that you would use a sentinel head and tail to simplify edge cases, and discuss how the modifications might affect concurrency or eviction policies.
Ask questions to understand the specific modifications (e.g., time-based expiration, size limits, concurrency) and expected operations.
Propose using a hash map for O(1) key lookup and a doubly linked list to maintain access order, explaining how they interact.
Detail how get and put work, including moving nodes to the front and evicting from the tail, and how modifications are handled.
Compare with alternatives like arrays or singly linked lists, highlighting O(1) removal and insertion, and bidirectional traversal.
Address memory overhead, thread safety, and potential improvements like using a circular list or combining with other structures.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.