Google·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

May 2026

Summary

Google SWE coding round, one problem but it had legs. Started easy enough and then they kept pushing on complexity until I was drawing Union-Find on the whiteboard and second-guessing every word I said.

Questions Asked (1)

You have an integer array of length N and a list of queries, where each query (q1, q2, k) overwrites all elements in the inclusive index range [q1, q2] with value k. Queries are applied in order, so later ones overwrite earlier ones in overlapping regions. Return the final array, and be ready to discuss approaches better than the naive O(N * Q) solution.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I started with the brute force and they let me finish it, then immediately asked what happens when N and Q are both a million.

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AI HintsAI Generated

Suggested Approach

Start by acknowledging the naive O(N*Q) approach, then propose an optimized solution using a segment tree with lazy propagation or a reverse processing technique. Explain the trade-offs between time and space complexity, and discuss edge cases like overlapping queries and large N.

Pro tip: Mention that processing queries in reverse order can simplify the problem to O(N+Q) with a disjoint-set union (DSU) for skipping already assigned indices, which is often more efficient and easier to implement than a segment tree.

1. Clarify the problem

Restate the problem to ensure understanding: we have an array of size N, and Q queries each overwriting a range with a value. The final array is needed after all queries.

2. Discuss naive approach

Explain the straightforward O(N*Q) solution: for each query, iterate over the range and update the array. Mention its simplicity but poor scalability for large inputs.

3. Propose optimized approaches

Present two optimized methods: (1) Segment tree with lazy propagation for O(Q log N) time, and (2) Reverse processing with DSU for O(N+Q) time. Briefly explain how each works.

4. Compare trade-offs

Compare the approaches: segment tree is more general and handles online queries, while reverse DSU is simpler and faster for this specific offline problem. Discuss space complexity and implementation complexity.

5. Handle edge cases and conclude

Mention edge cases: empty array, queries with q1 > q2 (if allowed), overlapping ranges, and large values. Conclude with the recommended approach based on constraints.

Key Points to Mention

Time complexity: naive O(N*Q) vs optimized O(Q log N) or O(N+Q)
Space complexity: segment tree O(N) vs DSU O(N)
Lazy propagation in segment trees for range updates
Reverse processing with disjoint-set union (DSU) to skip assigned indices
Offline vs online processing: reverse DSU works only if all queries are known in advance
Edge cases: overlapping queries, full range overwrites, and large N

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