Tree Traversal Inorder Left Root Right in DSA Javascript - Time & Space Complexity

Time Complexity: Tree Traversal Inorder Left Root Right

O(n)

Understanding Time Complexity

We want to understand how the time needed to visit all nodes in a tree grows as the tree gets bigger.

How does the number of steps change when we do an inorder traversal (left, root, right)?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function inorderTraversal(node) {
  if (node === null) return;
  inorderTraversal(node.left);
  console.log(node.value);
  inorderTraversal(node.right);
}
    

This code visits each node in a binary tree in the order: left child, current node, then right child.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls visiting each node once.
• How many times: Exactly once per node in the tree.

How Execution Grows With Input

Each node is visited once, so the total steps grow directly with the number of nodes.

Input Size (n)	Approx. Operations
10	About 10 visits
100	About 100 visits
1000	About 1000 visits

Pattern observation: The work grows linearly as the tree size grows.

Final Time Complexity

Time Complexity: O(n)

This means the time to complete the traversal grows in direct proportion to the number of nodes.

Common Mistake

[X] Wrong: "The traversal takes more time because it calls itself twice each time, so it must be exponential."

[OK] Correct: Each node is visited only once, so the total steps add up to the number of nodes, not more.

Interview Connect

Understanding this traversal's time helps you explain how tree algorithms work efficiently and shows you can analyze recursive code clearly.

Self-Check

"What if we changed the traversal to preorder (root, left, right)? How would the time complexity change?"

Practice

1. What is the order of nodes visited in an inorder traversal of a binary tree?

easy

A. Root, Right subtree, Left subtree

B. Left subtree, Root, Right subtree

C. Right subtree, Root, Left subtree

D. Root, Left subtree, Right subtree

Solution

1. Step 1: Understand inorder traversal definition

   Inorder traversal visits nodes in the order: left subtree first, then the root node, and finally the right subtree.

2. Step 2: Match the traversal order to options

   Left subtree, Root, Right subtree correctly states the order as Left subtree, Root, Right subtree.

3. Final Answer:

   Left subtree, Root, Right subtree -> Option B

4. Quick Check:

   Inorder = Left, Root, Right [OK]

Hint: Inorder always visits left child before root [OK]

Common Mistakes:

• Confusing inorder with preorder or postorder
• Visiting root before left subtree
• Visiting right subtree before root

2. Which of the following is the correct JavaScript function signature for inorder traversal of a binary tree node named node?

easy

A. function inorder(node) { inorder(node.right); console.log(node.value); inorder(node.left); }

B. function inorder(node) { console.log(node.value); inorder(node.left); inorder(node.right); }

C. function inorder(node) { if(node) { inorder(node.left); console.log(node.value); inorder(node.right); } }

D. function inorder(node) { inorder(node.left); inorder(node.right); console.log(node.value); }

Solution

1. Step 1: Recall inorder traversal steps in code

   Inorder traversal visits left subtree, then root, then right subtree. So the function must call inorder on left, print root, then call inorder on right.

2. Step 2: Check each option's order

   function inorder(node) { if(node) { inorder(node.left); console.log(node.value); inorder(node.right); } } matches the correct order: left, root (console.log), right. Others have wrong orders.

3. Final Answer:

   function inorder(node) { if(node) { inorder(node.left); console.log(node.value); inorder(node.right); } } -> Option C

4. Quick Check:

   Left, Root, Right in code = function inorder(node) { if(node) { inorder(node.left); console.log(node.value); inorder(node.right); } } [OK]

Hint: Inorder prints after left call, before right call [OK]

Common Mistakes:

• Printing before left subtree traversal
• Swapping left and right subtree calls
• Missing null check for node

3. Given the binary tree below, what is the output of inorder traversal?

    10
   /  \
  5    15
 /    /  \
3    12  20

medium

A. [3, 5, 10, 12, 15, 20]

B. [10, 5, 3, 15, 12, 20]

C. [3, 5, 12, 10, 15, 20]

D. [5, 3, 10, 15, 12, 20]

Solution

1. Step 1: Traverse left subtree of root 10

   Left subtree of 10 is rooted at 5. Its left child is 3. Inorder of left subtree: visit 3, then 5 (root of subtree).

2. Step 2: Visit root 10 and then right subtree

   After left subtree, visit root 10. Then traverse right subtree rooted at 15: left child 12, root 15, right child 20. So inorder right subtree is 12, 15, 20.

3. Final Answer:

   [3, 5, 10, 12, 15, 20] -> Option A

4. Quick Check:

   Inorder = Left, Root, Right = [3,5,10,12,15,20] [OK]

Hint: List nodes left-root-right recursively [OK]

Common Mistakes:

• Visiting root before left subtree
• Mixing order of right subtree nodes
• Skipping leaf nodes

4. The following JavaScript code is intended to perform inorder traversal but has a bug. What is the bug?

function inorder(node) {
  if (node === null) return;
  console.log(node.value);
  inorder(node.left);
  inorder(node.right);
}

medium

A. It prints the root before left subtree, so not inorder

B. It does not check for null nodes

C. It misses traversing the right subtree

D. It calls inorder on left and right in wrong order

Solution

1. Step 1: Analyze the order of operations in code

   The code prints node.value first, then calls inorder on left and right. This is preorder traversal order.

2. Step 2: Identify correct inorder order

   Inorder traversal requires visiting left subtree first, then printing root, then right subtree. The code prints root before left subtree, which is incorrect.

3. Final Answer:

   It prints the root before left subtree, so not inorder -> Option A

4. Quick Check:

   Print after left call for inorder [OK]

Hint: Print after left subtree call for inorder [OK]

Common Mistakes:

• Printing root before left subtree
• Confusing preorder with inorder
• Not checking for null nodes (though code does here)

5. You have a binary search tree (BST) and want to get all values in ascending order using inorder traversal. Which of the following modifications to the inorder traversal function will correctly collect values into an array instead of printing them?

function inorder(node, arr) {
  if (!node) return;
  // Fill missing code here
}

hard

A. inorder(node.left, arr); inorder(node.right, arr); arr.push(node.value);

B. arr.push(node.value); inorder(node.left, arr); inorder(node.right, arr);

C. inorder(node.right, arr); arr.push(node.value); inorder(node.left, arr);

D. inorder(node.left, arr); arr.push(node.value); inorder(node.right, arr);

Solution

1. Step 1: Recall inorder traversal order for BST

   Inorder traversal visits left subtree, then root, then right subtree, which returns values in ascending order for BST.

2. Step 2: Choose code that collects values in correct order

   inorder(node.left, arr); arr.push(node.value); inorder(node.right, arr); calls inorder on left, then pushes current node value, then calls inorder on right, correctly collecting values in ascending order.

3. Final Answer:

   inorder(node.left, arr); arr.push(node.value); inorder(node.right, arr); -> Option D

4. Quick Check:

   Left, Root, Right with push = inorder(node.left, arr); arr.push(node.value); inorder(node.right, arr); [OK]

Hint: Push after left call, before right call for sorted array [OK]

Common Mistakes:

• Pushing before left subtree traversal
• Swapping left and right subtree calls
• Pushing after both subtree traversals