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Roblox·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Roblox coding round, tree traversal problem. Pretty clean question but the pre-order tie-breaking detail is the kind of thing that bites you if you're not careful.

Questions Asked (1)

Q1

Given a tree (binary or n-ary), find the node at the greatest depth. If there are multiple nodes at that depth, return whichever appears first in pre-order traversal.

Algorithms & Data Structures
Author's notes

The base problem is easy enough, just DFS and track depth.

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AI HintsAI Generated

Suggested Approach

Clarify the tree structure and traversal order, then propose a depth-first pre-order traversal that tracks the maximum depth and the first node encountered at that depth. Walk through a small example to verify the logic, then analyze time and space complexity.

Pro tip: Mention that pre-order traversal naturally visits nodes in the required order, so the first node at the maximum depth is automatically the correct answer. Also note that an iterative solution avoids recursion depth limits for very deep trees.

1. Clarify the problem

Confirm whether the tree is binary or n-ary, and whether 'greatest depth' means maximum number of edges from the root. Ask if the tree can be empty or have a single node.

2. Choose traversal strategy

Select a depth-first pre-order traversal (root, then children left-to-right) to ensure the first node at the maximum depth is found. Alternatively, use BFS level-order but track the first node at the last level.

3. Design the algorithm

Recursively or iteratively traverse the tree, passing the current depth. Maintain global variables for max depth and the corresponding node. Update only when a strictly greater depth is found.

4. Walk through an example

Trace the algorithm on a sample tree with multiple deepest nodes to demonstrate that the first one in pre-order is returned. Show how the max depth and node are updated.

5. Analyze complexity and edge cases

State O(n) time and O(h) space for recursion (or O(n) for iterative stack). Discuss edge cases: empty tree, single node, skewed tree, and multiple deepest nodes.

Key Points to Mention

  • Pre-order traversal order: root, then children left-to-right, ensures the first deepest node is found.
  • Tracking maximum depth and the corresponding node with global variables or a helper class.
  • Time complexity O(n) and space complexity O(h) for recursion, where h is tree height.
  • Handling edge cases: empty tree (return null), single node (return root), and multiple deepest nodes.
  • Iterative DFS with an explicit stack to avoid recursion depth limits for very deep trees.
  • Comparison with BFS: BFS can also work but requires tracking the first node at the last level.

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