Snowflake·Software Engineer·Technical Phone Screen·Senior

Senior

Jul 2026

Summary

Snowflake software engineer interview with a pretty focused algorithmic problem around binary trees. The question had enough layers to it that I kept second-guessing my approach the whole time.

Questions Asked (1)

Given two complete binary trees with identical structure, update each node in the second tree so its value equals the sum of all values in the subtree rooted at the corresponding position in the first tree. The solution must run in linear time and use at most O(h) extra space where h is the tree height.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was a straightforward recursive postorder traversal, compute subtree sums in tree one and assign them to tree two simultaneously.

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AI HintsAI Generated

Suggested Approach

Use a simultaneous post-order traversal of both trees, computing subtree sums from the first tree and writing them into the second tree. Since the trees have identical structure, you can recurse in lockstep, and the recursion stack naturally uses O(h) space.

Pro tip: Emphasize that the O(h) space is due to the recursion stack, and if the tree is skewed, h can be O(n), but the problem allows O(h) space. Also, mention that an iterative approach with an explicit stack would also achieve O(h) space.

1. Clarify the problem and constraints

Confirm that the trees are complete and have identical structure, and that we need to update the second tree in-place. Note that the solution must be O(n) time and O(h) space.

2. Choose a traversal strategy

Select a post-order traversal because subtree sums require children's sums first. Traverse both trees simultaneously to avoid extra space for mapping.

3. Define the recursive function

Write a function that takes nodes from both trees. If both are null, return 0. Recursively compute left and right sums from the first tree, set the second node's value to the sum of its left and right sums plus the first node's value, and return that sum.

4. Analyze complexity

Explain that each node is visited once, so time is O(n). The recursion depth is the height h, so space is O(h) due to the call stack.

5. Handle edge cases and test

Consider empty trees, single-node trees, and skewed trees. Walk through a small example to verify correctness.

Key Points to Mention

Post-order traversal ensures children are processed before parents.
Simultaneous traversal of both trees leverages identical structure.
In-place update of the second tree avoids extra space.
Time complexity O(n) because each node is visited once.
Space complexity O(h) due to recursion stack, which is optimal for this problem.
The solution works for any binary tree, not just complete ones, as long as structures match.

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