The sorting part was fine, stable sort by score and move on.
First, clarify the requirements and edge cases, then outline a two-phase algorithm: sort by score descending, then scan to group consecutive photos into batches of up to 3, and finally re-sort the merged items by their representative scores. Discuss time/space complexity and potential optimizations, and relate the problem to real-world feed ranking at Nextdoor.
Pro tip: Emphasize that the grouping must be done on the already sorted list to ensure consecutive photos are batched, and that the batch's score is the first photo's score—this preserves the relative order when re-sorting. Also, mention that stable sorting or a tie-breaking rule may be needed for equal scores.
Ask about input size, score ties, empty lists, and whether photos can be grouped across non-photo items. Confirm that batches are formed only from consecutive photos in the sorted list.
Sort the feed by score descending. Then iterate through the sorted list, grouping consecutive photos into batches of up to 3. Each batch becomes a single item with score equal to the first photo's score.
Collect all non-photo items and photo batches into a new list, then sort this list by score descending. Ensure that the original order of items with equal scores is preserved if needed.
Discuss time complexity: O(n log n) due to sorting. Space complexity: O(n). Consider if a single pass with a priority queue could work, but note that grouping requires sorted order.
Walk through a small example to verify correctness, including edge cases like all photos, no photos, and ties in scores.
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