Maven Clinic·Software Engineer·Technical Phone Screen·Senior

Senior

Jun 2026

Summary

Maven Clinic system design question focused on a paginated listing problem with a diversity constraint. Single question, pretty deep, took up most of the session.

Questions Asked (1)

You have a pre-sorted list of clinic records (each with a payer_id, listing_id, rating, and other fields). Paginate them into pages of x items, maximizing payer_id diversity per page so the same payer doesn't appear twice on a page if avoidable. Describe your algorithm, its time complexity, and how you handle the edge case where one payer has more records than remaining page slots.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs

Author's notes

I went with a greedy approach: iterate through the sorted list and fill each page slot with the next record whose payer_id isn't already on that page.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and constraints, then propose a greedy round-robin approach that cycles through payers to fill each page, ensuring diversity. Explain how to handle the edge case where one payer dominates by either allowing duplicates or adjusting page composition, and analyze time and space complexity.

Pro tip: Mention that since the list is pre-sorted, you can group records by payer in O(n) time, and then use a round-robin pointer to efficiently select records for each page. Also, discuss the trade-off between strict diversity and page size when a payer has too many records.

1. Clarify Requirements and Constraints

Ask about the definition of 'maximizing diversity', whether duplicates are allowed if unavoidable, and if the original order within a payer must be preserved. Confirm page size x and whether pages must be filled completely.

2. Preprocess the Sorted List

Since the list is sorted, group records by payer_id into a list of queues or arrays, each containing records for one payer. This takes O(n) time and O(n) space.

3. Greedy Round-Robin Selection

For each page, iterate through the payer groups in a round-robin fashion, taking one record from each payer until the page is full. Skip payers that have no remaining records. This ensures maximum diversity per page.

4. Handle Edge Case: Dominant Payer

If a payer has more records than remaining slots on a page, after all other payers are exhausted, fill the remaining slots with records from that payer. This may result in duplicates on the page, but it's unavoidable. Alternatively, if strict diversity is required, leave slots empty or adjust page size.

5. Analyze Complexity and Optimize

Time complexity: O(n) for grouping + O(n) for round-robin selection = O(n). Space complexity: O(n) for storing groups. Discuss potential optimizations like using a min-heap to always pick from the payer with the most remaining records, but note that round-robin is simpler and sufficient.

Key Points to Mention

Greedy round-robin approach ensures maximum diversity by cycling through payers.
Time complexity O(n) and space complexity O(n) due to grouping.
Edge case handling: when one payer has more records than remaining slots, fill with that payer, possibly causing duplicates.
Trade-off between strict diversity and page fullness; may need to allow duplicates or leave slots empty.
Preservation of original order within each payer's records.
Potential alternative: use a priority queue (max-heap) to always pick from the payer with most remaining records, but round-robin is simpler and equally effective for diversity.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.