Invert Binary Tree

Data Structures
Easy
Netflix
43.5K views

Given the root of a binary tree, invert the tree (i.e., mirror it) and return its root. Implement using either recursion or iteration.

Why Interviewers Ask This

Netflix values engineers who write clean, maintainable code and understand fundamental data manipulation deeply. This question tests your ability to visualize tree structures, choose between recursion and iteration effectively, and handle pointer manipulation without corrupting the original structure. It reveals if you can implement a core algorithm with optimal time complexity while maintaining code readability.

How to Answer This Question

1. Clarify the problem by defining what 'inverting' means: swapping left and right children for every node in the tree. Ask about edge cases like an empty root or single-node trees immediately. 2. Propose two approaches: a recursive solution which is concise and natural for trees, and an iterative approach using a stack or queue for breadth-first traversal. Explain that Netflix often prefers clarity, so recursion is usually acceptable here unless memory constraints are specified. 3. Walk through a small example on a whiteboard or shared editor, showing how the swap happens at each level before moving down. 4. Write clean pseudocode or actual code, ensuring variable names are descriptive (e.g., 'temp', 'leftChild', 'rightChild'). 5. Analyze complexity explicitly: state that time complexity is O(n) since every node is visited once, and space complexity is O(h) for recursion stack or O(w) for the queue, where h is height and w is width.

Key Points to Cover

  • Explicitly define the swapping logic before writing any code
  • Demonstrate understanding of base cases for recursion
  • Correctly identify O(n) time complexity for visiting all nodes
  • Discuss space complexity trade-offs between recursion and iteration
  • Mention handling null pointers to prevent runtime errors

Sample Answer

To invert this binary tree, I need to swap the left and right children of every node recursively. Let's start by handling the base case: if the root is null, we simply return null. Otherwise, I'll create a temporary variable to hold the current left child, assign the right child to the left position, and then assign the temporary variable to the right position. After performing this swap, I will recursively call the function on both the new left and right subtrees. For example, if we have a root with value 4, left child 2, and right child 7, after the first step, 4's left becomes 7 and right becomes 2. Then we recurse into those nodes. If we chose an iterative approach instead, we would use a queue to perform a level-order traversal, swapping children as we dequeue each node. This ensures we process every node exactly once. The time complexity for either approach is O(n) because we visit every node in the tree. The space complexity depends on the implementation; recursion uses O(h) space for the call stack, where h is the tree height, while the iterative queue method uses O(w) space, where w is the maximum width of the tree. Given Netflix's focus on scalable and readable systems, I would likely present the recursive solution first for its elegance, but be prepared to discuss the iterative version if deep recursion stacks were a concern in their specific infrastructure context.

Common Mistakes to Avoid

  • Forgetting to swap children before recursing, causing infinite loops or incorrect results
  • Modifying the original tree structure incorrectly by losing references during the swap
  • Ignoring edge cases like an empty tree or a tree with only one node
  • Failing to analyze space complexity differences between recursive and iterative solutions

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