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Google·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say
May 2026Remote

Summary

Google SWE coding round with a sliding window / sorted structure problem about packing items from a conveyor belt into triplets. The problem sounded deceptively manageable at first glance but the online nature of it (streaming input, immediate output, removal) added real complexity.

Questions Asked (1)

Q1

Design a class that accepts a stream of integer item sizes and, whenever any three stored items satisfy max minus min being strictly less than a given threshold, immediately returns one such sorted triplet and removes those three items from storage.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I jumped straight to a sorted structure which was the right instinct, but I fumbled explaining why removal had to happen atomically and how I'd find the triplet efficiently.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and requirements first, then propose a solution using a balanced BST or two heaps to maintain sorted order and efficiently find valid triplets. Discuss trade-offs between different data structures and algorithms, and analyze time and space complexity.

Pro tip: Mention that you can optimize by checking only consecutive elements in sorted order, since if any triplet satisfies the condition, three consecutive elements will also satisfy it. This shows deep insight and can simplify the implementation.

1. Clarify Requirements and Constraints

Ask about the expected frequency of operations, memory constraints, and whether the threshold is fixed or can change. Confirm that the triplet must be sorted and removed immediately upon detection.

2. Choose Data Structures

Propose using a balanced binary search tree (e.g., TreeSet in Java) or two heaps (min-heap and max-heap) to maintain sorted order and allow efficient insertion and deletion. Discuss the trade-offs between these options.

3. Design the Algorithm

After each insertion, check for a valid triplet. Since any valid triplet implies three consecutive elements in sorted order also satisfy the condition, check consecutive triples in the sorted structure. If found, return and remove them.

4. Analyze Complexity

Analyze the time complexity of insertion, checking, and removal. For a balanced BST, insertion and deletion are O(log n), and checking consecutive triples can be done in O(1) if we maintain pointers or O(k) where k is the number of elements, but we can optimize by checking only around the inserted element.

5. Discuss Optimizations and Edge Cases

Consider optimizations like lazy deletion or maintaining a separate structure for quick min/max access. Handle edge cases such as fewer than three items, multiple valid triplets, and duplicate values.

Key Points to Mention

  • Use of balanced BST (e.g., TreeSet) or two heaps to maintain sorted order
  • Key insight: checking consecutive elements in sorted order is sufficient
  • Time complexity: O(log n) for insertion and deletion, O(1) or O(log n) for checking
  • Space complexity: O(n) for storing items
  • Handling duplicates and ensuring strict inequality (max - min < threshold)
  • Trade-offs between different data structures and potential optimizations

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