Tree Traversal Inorder Left Root Right in DSA Typescript - 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 the tree has more nodes?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

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

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

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls to visit each node once.
• How many times: Once per node in the tree.

How Execution Grows With Input

Each node is visited exactly one time, 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 in a straight line with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to complete the traversal grows directly with the number of nodes in the tree.

Common Mistake

[X] Wrong: "Since the function calls itself twice, the time complexity is exponential like O(2^n)."

[OK] Correct: Each node is visited only once, so the total work is just one visit per node, not doubling each time.

Interview Connect

Understanding tree traversal time helps you explain how algorithms handle hierarchical data efficiently, a common skill in many coding challenges.

Self-Check

"What if we changed inorder traversal to preorder traversal? 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. Left subtree, Root, Right subtree

B. Root, Left subtree, Right subtree

C. Right subtree, Root, Left subtree

D. Root, Right subtree, Left 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 A

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 TypeScript function signatures correctly represents an inorder traversal function for a binary tree node?

easy

A. function inorder(node: TreeNode): number[]

B. function inorder(node: TreeNode | null): void

C. function inorder(): void

D. function inorder(node: TreeNode | null): number

Solution

1. Step 1: Analyze function parameters and return type

   An inorder traversal function typically takes a node or null as input and performs traversal, often printing or processing nodes without returning a value.

2. Step 2: Check options for correct signature

   function inorder(node: TreeNode | null): void accepts a node or null and returns void, which fits traversal that prints or processes nodes.

3. Final Answer:

   function inorder(node: TreeNode | null): void -> Option B

4. Quick Check:

   Traversal function takes node or null, returns void [OK]

Hint: Traversal functions usually take node or null, return void [OK]

Common Mistakes:

• Omitting null in parameter type
• Returning incorrect types like number or array
• Missing parameter in function signature

3. Given the following binary tree:

    2
   / \
  1   3

What is the output of inorder traversal printing node values?

medium

A. [2, 1, 3]

B. [3, 2, 1]

C. [1, 3, 2]

D. [1, 2, 3]

Solution

1. Step 1: Visualize the tree and inorder traversal

   Inorder visits left subtree, root, then right subtree. For root 2, left child is 1, right child is 3.

2. Step 2: List nodes in inorder

   Visit left: 1, then root: 2, then right: 3, so output is [1, 2, 3].

3. Final Answer:

   [1, 2, 3] -> Option D

4. Quick Check:

   Inorder of 2-node tree = [1, 2, 3] [OK]

Hint: Inorder prints nodes sorted for BST [OK]

Common Mistakes:

• Printing root before left subtree
• Swapping left and right subtree order
• Confusing preorder or postorder output

4. Consider this TypeScript inorder traversal function:

function inorder(node: TreeNode | null): void {
  if (node === null) return;
  inorder(node.right);
  console.log(node.val);
  inorder(node.left);
}

What is the main problem with this code?

medium

A. It prints node values twice

B. It does not handle null nodes properly

C. It visits right subtree before left, so traversal order is incorrect

D. It causes infinite recursion

Solution

1. Step 1: Analyze traversal order in code

   The function calls inorder on right subtree first, then prints root, then calls inorder on left subtree.

2. Step 2: Compare with correct inorder order

   Correct inorder is left subtree, root, right subtree. This code reverses left and right, so order is wrong.

3. Final Answer:

   It visits right subtree before left, so traversal order is incorrect -> Option C

4. Quick Check:

   Inorder must visit left before right [OK]

Hint: Inorder must call left subtree before right [OK]

Common Mistakes:

• Swapping left and right subtree calls
• Forgetting base case for null
• Printing before recursive calls

5. You have a binary tree where each node contains a number. You want to collect all node values in an array using inorder traversal. Which TypeScript code snippet correctly implements this?

hard

A. function inorder(node: TreeNode | null, arr: number[]): void {
if (!node) return;
inorder(node.left, arr);
arr.push(node.val);
inorder(node.right, arr);
}

B. function inorder(node: TreeNode | null, arr: number[]): void {
if (!node) return;
arr.push(node.val);
inorder(node.left, arr);
inorder(node.right, arr);
}

C. function inorder(node: TreeNode | null, arr: number[]): void {
if (!node) return;
inorder(node.right, arr);
arr.push(node.val);
inorder(node.left, arr);
}

D. function inorder(node: TreeNode | null): number[] {
if (!node) return [];
return [node.val].concat(inorder(node.left)).concat(inorder(node.right));
}

Solution

1. Step 1: Understand inorder traversal with array accumulation

   We must visit left subtree, then root (push value), then right subtree, passing the same array to collect values.

2. Step 2: Check each option for correct order and array usage

   function inorder(node: TreeNode | null, arr: number[]): void { if (!node) return; inorder(node.left, arr); arr.push(node.val); inorder(node.right, arr); } correctly visits left, pushes root value, then visits right, using the same array.

3. Final Answer:

   function inorder(node: TreeNode | null, arr: number[]): void { if (!node) return; inorder(node.left, arr); arr.push(node.val); inorder(node.right, arr); } -> Option A

4. Quick Check:

   Left, root, right with shared array [OK]

Hint: Push node value after left subtree call [OK]

Common Mistakes:

• Pushing before left subtree traversal
• Swapping left and right subtree calls
• Returning new arrays instead of using passed array