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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Meta SWE coding round with two LeetCode-style problems. Nothing too wild but both questions required some thought, not just pattern matching.

Questions Asked (2)

Q1

Given a string of parentheses and letters, remove the minimum number of parentheses to make the string valid.

Algorithms & Data Structures
Author's notes

Stack-based approach is the move here.

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AI HintsAI Generated

Suggested Approach

Clarify the problem and constraints, then propose a stack-based solution that tracks unmatched parentheses. Explain that you can remove invalid parentheses in a single pass by marking indices to delete, and discuss time/space complexity.

Pro tip: Mention that the problem can be solved in O(n) time with O(n) space using a stack, but also note that a two-pass counting approach can achieve O(1) space if only the count of removals is needed. This shows awareness of optimization trade-offs.

1. Clarify and Confirm

Ask clarifying questions: Are there multiple valid answers? Should we return the string or just the minimum number? Are there other characters besides parentheses and letters? Confirm that letters are ignored and only parentheses matter.

2. Outline Approach

Propose using a stack to track indices of unmatched opening parentheses. Iterate through the string, push indices of '(' and pop for ')' when possible; after traversal, mark remaining stack indices and any unmatched ')' for removal.

3. Walk Through Example

Trace the algorithm on a sample input like 'a)b(c)d' to demonstrate how invalid parentheses are identified and removed, resulting in 'ab(c)d'.

4. Analyze Complexity

State that the algorithm runs in O(n) time and uses O(n) space for the stack and a boolean array to mark removals. Mention that space can be reduced to O(1) if only the count is needed.

5. Discuss Edge Cases

Cover edge cases: empty string, string with only letters, all opening or all closing parentheses, and nested valid parentheses. Explain how the algorithm handles each.

Key Points to Mention

  • Use a stack to track indices of unmatched opening parentheses.
  • Mark unmatched closing parentheses during iteration.
  • Build the result by skipping marked indices.
  • Time complexity: O(n), space complexity: O(n).
  • Alternative two-pass counting approach for O(1) space if only count is needed.
  • Letters are ignored and do not affect validity.

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

Q2

In a binary tree, find all nodes that are exactly K edges away from a given target node.

Algorithms & Data Structures
Author's notes

Trickier than it looks because you can go up the tree too, not just down.

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AI HintsAI Generated

Suggested Approach

Treat the tree as an undirected graph and perform a BFS from the target node, tracking distance until K edges are reached. Alternatively, use a two-phase DFS: first find the path from root to target, then for each ancestor at distance d from target, explore the subtree of the other child to a depth of K-d-1. Both approaches run in O(N) time.

Pro tip: Clarify whether the tree is a binary tree (each node has at most two children) and whether nodes are unique. Also, mention that if K=0, the answer is just the target node itself, and if K exceeds the tree height, the result is empty.

1. Clarify the problem

Confirm the definition of 'K edges away' and whether the tree is rooted or unrooted. Ask if nodes are unique and if the target node is guaranteed to exist.

2. Choose an approach

Decide between BFS on the undirected graph (simpler, uses extra space for parent pointers) or DFS with path tracking (more space-efficient, but requires careful implementation).

3. Implement the solution

For BFS: build parent pointers, then BFS from target, stopping at distance K. For DFS: find the path from root to target, then for each ancestor, explore the other subtree to depth K - distance - 1.

4. Analyze complexity

State that both approaches run in O(N) time and O(N) space in the worst case (for BFS, space is O(N) for the queue and parent map; for DFS, space is O(H) for recursion stack plus O(H) for path).

5. Test with edge cases

Consider K=0, K larger than tree height, target at root, target at leaf, and skewed trees. Verify that the solution handles these correctly.

Key Points to Mention

  • BFS on the tree treated as an undirected graph using parent pointers
  • Two-phase DFS: find path from root to target, then explore subtrees at appropriate depths
  • Time complexity O(N) and space complexity O(N) for both approaches
  • Handling edge cases: K=0, K > height, target at root/leaf
  • Avoiding revisiting nodes by tracking the parent or using a visited set
  • Clarifying assumptions about tree structure and node uniqueness

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