← Meta Interview Insights

Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Meta SWE coding round with a twist on a classic tree problem. The variant they threw in made it less straightforward than I expected.

Questions Asked (1)

Q1

Given a binary tree, perform a vertical order traversal where each column has a computed weight. Sort the output by those column weights rather than by standard column index.

Algorithms & Data Structures
Author's notes

I knew vertical order traversal cold but the weighting part tripped me up for a bit.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the definition of column weight and how it's computed, then use a BFS/DFS to group nodes by column index while tracking weights. Finally, sort the columns by weight and output the nodes in that order.

Pro tip: Discuss trade-offs between BFS and DFS for vertical order, and mention that if weights are dynamic, a priority queue might be needed; also, confirm if nodes within a column should be sorted by row or value.

1. Clarify the problem

Ask how column weight is defined (e.g., sum of node values, count of nodes) and whether ties in weight should be broken by column index or another rule.

2. Choose traversal and data structures

Use BFS or DFS to traverse the tree, maintaining a map from column index to a list of nodes and a running weight for each column.

3. Compute weights and collect nodes

During traversal, update the weight for each column and append nodes to the corresponding list, ensuring order within a column (e.g., by row).

4. Sort columns by weight

Extract the column indices and their weights, sort them by weight (and tie-breaker if specified), then output the nodes in that order.

5. Analyze complexity and edge cases

Discuss time and space complexity, and handle edge cases like empty tree, negative weights, or columns with equal weights.

Key Points to Mention

  • Definition of column weight (e.g., sum of node values, node count) and tie-breaking rules.
  • Choice of traversal (BFS vs DFS) and its impact on ordering within columns.
  • Use of hash map to group nodes by column index and track weights.
  • Sorting columns by weight, considering stability and tie-breakers.
  • Time and space complexity analysis (e.g., O(N log N) due to sorting).
  • Handling edge cases: empty tree, single node, skewed tree, negative weights.

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