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Citadel·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Coding round at Citadel for a software engineering role. Second half of the session was a tree path problem, basically a twist on the classic path sum problem but asking for the minimum instead.

Questions Asked (1)

Q1

Given a binary tree, find the path from root to leaf with the minimum sum and return that sum.

Algorithms & Data Structures
Author's notes

It's a variant of the standard path sum problem.

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AI HintsAI Generated

Suggested Approach

Use a depth-first search (DFS) to traverse the tree, maintaining the current path sum. At each leaf, compare the sum with the minimum found so far and update accordingly. Return the minimum sum after the traversal.

Pro tip: Clarify edge cases upfront, such as an empty tree or negative values, and discuss how your solution handles them. Mention that you can optimize space by not storing all paths, only the current sum.

1. Clarify the problem

Ask if the tree can be empty, if node values can be negative, and if the path must end at a leaf (node with no children). Confirm the definition of 'minimum sum'.

2. Choose traversal method

Decide between recursive DFS or iterative stack-based DFS. Explain that DFS is suitable because it explores each root-to-leaf path exactly once.

3. Design the algorithm

Outline a recursive function that takes a node and the current sum. If the node is a leaf, update the global minimum. Otherwise, recurse on left and right children with the updated sum.

4. Analyze complexity

State that time complexity is O(n) since each node is visited once, and space complexity is O(h) for the recursion stack, where h is the tree height.

5. Handle edge cases

Discuss how to handle an empty tree (return 0 or infinity depending on definition) and trees with negative values (the algorithm still works).

Key Points to Mention

  • DFS traversal to explore all root-to-leaf paths
  • Maintaining current sum and updating global minimum at leaves
  • Time complexity O(n) and space complexity O(h)
  • Handling edge cases: empty tree, single node, negative values
  • Avoiding unnecessary path storage to save space
  • Potential for iterative solution to avoid recursion stack overflow

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