Binary Tree Inorder Traversal

Binary Tree Inorder Traversal

What is this problem about?

The Binary Tree Inorder Traversal interview question is a cornerstone of computer science fundamentals. It asks you to visit all the nodes of a binary tree in a specific order: Left subtree, then the Root, then the Right subtree. For a Binary Search Tree (BST), this traversal is particularly significant because it retrieves the values in non-decreasing sorted order. The challenge often lies not just in implementing it recursively, but in demonstrating an iterative approach using a stack or understanding the memory implications of each method.

Why is this asked in interviews?

This is a standard "gatekeeper" question asked by companies like Meta, Microsoft, and Amazon. It ensures that a candidate has a solid grasp of recursion and stack-based data structures. Interviewers use the Binary Tree Inorder Traversal coding problem to see if you understand how the call stack works. If you can implement the iterative version, it shows you can manage state manually, which is a vital skill for system-level programming and optimizing performance-critical applications.

Algorithmic pattern used

The core pattern is the Stack interview pattern or Recursion. In the recursive approach, the function calls itself for the left child, processes the current node, and then calls itself for the right child. In the iterative approach, you use an explicit stack to keep track of the "path" taken, allowing you to backtrack to the parent node after exploring the leftmost leaf.

Example explanation

Let's consider a simple tree: 10 /
5 15 / 2 7

Inorder traversal follows Left -> Root -> Right:

1. Start at 10, go left to 5.
2. At 5, go left to 2.
3. 2 has no children, so record [2].
4. Back to root 5, record [2, 5].
5. Go to 5's right child 7. Record [2, 5, 7].
6. Back to original root 10. Record [2, 5, 7, 10].
7. Go to 10's right child 15. Record [2, 5, 7, 10, 15]. The result is a sorted list of values.

Common mistakes candidates make

The most common mistake in the iterative version is getting the nested loop logic wrong—specifically, when to push to the stack and when to pop. Another mistake is forgetting to update the "current" node pointer after popping from the stack. In recursive solutions, candidates sometimes forget the base case (checking if the node is null), leading to a stack overflow.

Interview preparation tip

Don't stop at the recursive solution. While recursion is elegant, many interviewers will immediately ask, "Can you do this without recursion?" Practice the iterative version until the logic of "go left as far as possible, then pop and go right" becomes second nature. Also, look into Morris Traversal if you want to impress with an $O(1)$ space solution.