The carousel mechanics themselves weren't the hard part.
Start by clarifying requirements (e.g., circular vs. bounded, autoplay behavior, UI framework) and then design a clean API that separates state management from rendering. Use a circular buffer or doubly linked list for O(1) navigation, and a timer for autoplay with pause/resume. Analyze time/space complexity for each operation and discuss trade-offs.
Pro tip: Mention that autoplay should pause on user interaction (hover/focus) and resume after a delay—this shows attention to UX and real-world edge cases. Also, consider using requestAnimationFrame for smooth transitions instead of setInterval for better performance.
Ask about the environment (web, mobile), expected features (infinite loop, indicators, touch support), and performance constraints. Confirm if autoplay should pause on interaction and if the interval is configurable at runtime.
Choose a data structure for storing images and current index. A circular buffer (array with modulo) or doubly linked list gives O(1) next/prev. For autoplay, use a timer ID and a boolean flag for playing state.
Outline public methods: next(), prev(), goTo(index), play(), pause(), setInterval(ms). Include event callbacks for slide change and autoplay state. Ensure methods handle edge cases (e.g., empty list, single image).
Navigation is O(1) time, O(n) space for storing images. Autoplay uses O(1) additional space for timer. Discuss trade-offs: array vs. linked list (cache locality vs. dynamic size).
Address rapid clicking, timer drift, memory leaks (clear timers on destroy), and accessibility (keyboard navigation, ARIA). Suggest optimizations like lazy loading images and using CSS transitions.
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I went with cursor-based pagination pretty confidently since offset pagination breaks when comments get deleted mid-session.
Start by clarifying requirements (e.g., comment nesting, edit history, moderation) and then outline the data model and API endpoints. Focus on RESTful design with cursor-based pagination for scalability, and discuss trade-offs for edit/delete semantics.
Pro tip: Mention soft deletes and edit history to handle audit and moderation needs, and use cursor-based pagination with a stable sort order to avoid duplicates or missing items during concurrent updates.
Ask about comment threading (flat vs nested), edit/delete permissions, and expected scale to tailor the design.
Define entities like Comment with fields: id, image_id, user_id, content, created_at, updated_at, parent_id (for replies), and is_deleted flag.
List CRUD endpoints: POST /images/{image_id}/comments, GET /images/{image_id}/comments, PATCH /comments/{comment_id}, DELETE /comments/{comment_id}.
Use cursor-based pagination with parameters like limit and cursor (e.g., last comment ID or timestamp) to efficiently fetch comments in order.
Address soft vs hard deletes, edit history, rate limiting, and consistency models to show depth.
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This is where I spent most of my time and also where I felt shakiest.
Start by clarifying requirements and scale, then propose a data model that separates vote storage from comment metadata to handle high write throughput. For top-k retrieval, use a combination of per-image heaps or sorted sets with lazy updates, and discuss trade-offs between real-time and batch processing.
Pro tip: Mention that you would use a write-optimized store for votes (e.g., Cassandra) and a read-optimized cache (e.g., Redis sorted sets) for top-k, and that you would handle ties by including timestamp in the sort key. This shows you think about both write and read paths at scale.
Ask about read/write patterns, latency requirements, consistency needs, and whether votes can be changed or removed. Confirm the scale: 100k images, 1M comments, and potentially many votes per comment.
Propose separate storage for votes (e.g., a wide-column store keyed by comment_id) and comments (e.g., a relational or document store). Include fields like comment_id, image_id, score, created_at, and upvote/downvote counts.
For each image, maintain a sorted set (e.g., Redis ZSET) of comment_ids scored by (score, timestamp). Use a heap or sorted set to efficiently retrieve top-k. Discuss how to update the set on vote changes.
Discuss sharding by image_id, caching top-k results, and handling hot images. Compare real-time updates vs. batch recomputation, and explain how to handle ties and vote changes.
Wrap up with a coherent design, mention potential bottlenecks, and suggest extensions like pagination, time-decay scoring, or anti-abuse measures.
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Start by clarifying the requirements and constraints, then propose a layered solution combining client-side debouncing, idempotent server operations, and database-level constraints. Discuss trade-offs between consistency, latency, and complexity, and how you would handle edge cases like network retries.
Pro tip: Emphasize idempotency keys and atomic database operations as the core defense, and mention that client-side throttling alone is insufficient because users can bypass it or have multiple devices.
Ask about expected scale, consistency requirements, and whether the vote count needs to be exact in real-time. This shows you understand the problem context before jumping to solutions.
Propose debouncing or throttling UI events to reduce the number of requests sent. Acknowledge this is a first line of defense but not sufficient alone.
Design the vote endpoint to be idempotent using a unique request ID or idempotency key. The server should recognize duplicate requests and return the same response without applying the vote twice.
Use database transactions with conditional updates (e.g., INSERT ... ON CONFLICT DO NOTHING) or unique constraints on (user_id, comment_id) to ensure a user can only vote once. This prevents double-counting even if requests slip through.
Discuss network retries, distributed systems (e.g., using a distributed lock or consensus), and the trade-off between strong consistency and availability. Mention monitoring and alerting for anomalies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.