Tree Traversal Toolkit

This article covers the intuition, workflow, dry run, C++ implementation, complexity, and interview usage for Tree Traversal Toolkit.

1. Intuition

Traversal is how you visit nodes in a meaningful order:

• preorder: node before children
• inorder: left, node, right
• postorder: children before node
• level order: breadth-first by depth

2. How It Works

1. Pick the traversal that matches the information you need
2. Recurse or use an explicit stack or queue
3. Record values in the chosen order

3. Pattern Recognition

Think traversal when you see:

• visit all nodes
• print tree order
• build or validate BST behavior
• process nodes level by level

4. Dry Run Example

Input:

    2
   / \
  1   3

Step-by-step execution:

• Inorder: 1, 2, 3
• Preorder: 2, 1, 3
• Postorder: 1, 3, 2
• Level order: 2, 1, 3

5. Code (C++)

void inorder(TreeNode* root, vector<int>& result) {
  if (root == nullptr) {
    return;
  }

  inorder(root->left, result);
  result.push_back(root->val);
  inorder(root->right, result);
}

6. Complexity Analysis

• Time Complexity: O(n)
• Space Complexity: O(h) recursion stack

7. When to Use

• BST sorted order with inorder
• root-first construction with preorder
• deletion or accumulation with postorder
• shortest-level tasks with BFS

8. Common Mistakes

• mixing up traversal meanings
• ignoring null base cases

9. Variations / Extensions

• iterative traversals
• Morris traversal
• zigzag level order

10. LeetCode Practice Problems

Easy

• https://magicsheet.dev/questions/binary-tree-inorder-traversal/
• https://magicsheet.dev/questions/binary-tree-level-order-traversal/

11. Key Takeaways

• Traversal order should match the problem's information flow
• Inorder is especially important for BST questions

Back: Recursion, Backtracking, and Trees