← Meta Interview Insights

Meta·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Meta coding round, tree problem that looked familiar until it wasn't. The twist on the classic consecutive sequence question tripped me up more than I expected.

Questions Asked (1)

Q1

Given the root of a binary tree, find the longest strictly increasing top-down path (each child's value must be greater than its parent's) and return the actual sequence of node values, not just the length.

Algorithms & Data Structures
Author's notes

I'd seen the length version before so I felt pretty good at first.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Use a depth-first search (DFS) that traverses the tree while maintaining the current increasing path. At each node, if the node's value is greater than the parent's, extend the current path; otherwise, start a new path with the current node. Track the longest path found and return its sequence of values.

Pro tip: Clarify whether the path must be strictly increasing and whether it can start at any node. Also, discuss how to handle large trees to avoid stack overflow, possibly using iterative DFS.

1. Clarify requirements and edge cases

Confirm that the path is strictly increasing top-down, can start at any node, and that we need to return the actual sequence. Discuss edge cases like empty tree, single node, and negative values.

2. Choose traversal method

Decide between recursive DFS (simpler) or iterative DFS (avoids recursion limit). Explain the trade-offs and pick one based on constraints.

3. Design DFS with path tracking

At each node, compare its value with the parent's. If greater, append to current path; else, start a new path with the current node. Update the longest path if the current path is longer.

4. Implement and test

Write clean code with helper functions. Test with various trees: increasing chain, decreasing chain, mixed, and single node.

5. Analyze complexity and optimize

Time complexity is O(n) since each node is visited once. Space complexity is O(h) for recursion stack, where h is tree height. Discuss potential optimizations if needed.

Key Points to Mention

  • Strictly increasing condition: child value > parent value.
  • Path can start at any node, not necessarily root.
  • Need to return the sequence, not just length.
  • DFS is natural for path problems in trees.
  • Time complexity O(n), space O(h) for recursion.
  • Edge cases: empty tree, single node, negative values.

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