Validate if Tree is BST in DSA Javascript - Time & Space Complexity

Time Complexity: Validate if Tree is BST

O(n)

Understanding Time Complexity

We want to know how long it takes to check if a tree follows the rules of a Binary Search Tree (BST).

How does the time needed grow when the tree gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

function isBST(node, min = -Infinity, max = Infinity) {
  if (!node) return true;
  if (node.value <= min || node.value >= max) return false;
  return isBST(node.left, min, node.value) && isBST(node.right, node.value, max);
}
    

This code checks if a binary tree is a BST by making sure every node's value fits between allowed min and max limits.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

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

How Execution Grows With Input

As the number of nodes grows, the function visits each node one time.

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

Pattern observation: The time grows directly with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to check grows in a straight line with the number of nodes in the tree.

Common Mistake

[X] Wrong: "Checking only the immediate children is enough to confirm a BST."

[OK] Correct: Because a node deeper in the tree might break the BST rule, so we must check all nodes with proper min and max limits.

Interview Connect

Understanding this helps you show how to carefully check all parts of a tree, a skill useful in many tree problems.

Self-Check

"What if we remove the min and max limits and only compare a node with its immediate children? How would the time complexity and correctness change?"

Practice

1. What does it mean for a binary tree to be a Binary Search Tree (BST)?

easy

A. Every node has exactly two children

B. Every node's left child is smaller and right child is larger than the node

C. All nodes have the same value

D. The tree is balanced with equal height on both sides

Solution

1. Step 1: Understand BST property

   A BST requires that for each node, all nodes in the left subtree have smaller values and all nodes in the right subtree have larger values.

2. Step 2: Compare options with definition

   Every node's left child is smaller and right child is larger than the node correctly states this property. Other options describe different tree properties.

3. Final Answer:

   Every node's left child is smaller and right child is larger than the node -> Option B

4. Quick Check:

   BST property = Every node's left child is smaller and right child is larger than the node [OK]

Hint: BST means left < node < right for every node [OK]

Common Mistakes:

• Confusing BST with balanced tree
• Thinking all nodes must have two children
• Assuming all values are equal

2. Which of the following JavaScript function signatures is correct to check if a binary tree is a BST?

easy

A. function isBST(node, min, max) {}

B. function isBST(node, left, right, parent) {}

C. function checkBST(root) {}

D. function validateBST(tree, minVal) {}

Solution

1. Step 1: Identify common BST validation parameters

   To validate BST, we usually pass the current node and allowed min and max values to check constraints.

2. Step 2: Match function signatures

   function isBST(node, min, max) {} matches this pattern with node, min, and max parameters. Others have extra or missing parameters.

3. Final Answer:

   function isBST(node, min, max) {} -> Option A

4. Quick Check:

   Correct BST function signature = function isBST(node, min, max) {} [OK]

Hint: Use min and max limits to check BST recursively [OK]

Common Mistakes:

• Adding unnecessary parameters
• Missing min or max limits
• Using wrong parameter names

3. What will be the output of the following code snippet?

class Node {
  constructor(val, left = null, right = null) {
    this.val = val;
    this.left = left;
    this.right = right;
  }
}

function isBST(node, min = -Infinity, max = Infinity) {
  if (!node) return true;
  if (node.val <= min || node.val >= max) return false;
  return isBST(node.left, min, node.val) && isBST(node.right, node.val, max);
}

const root = new Node(10, new Node(5), new Node(15, new Node(6), new Node(20)));
console.log(isBST(root));

medium

A. undefined

B. true

C. false

D. TypeError

Solution

1. Step 1: Analyze tree structure

   Root is 10, left child 5 (valid), right child 15 with left child 6 and right child 20.

2. Step 2: Check BST property on right subtree

   Node 6 is left child of 15 but 6 < 10, which violates BST property because all right subtree nodes must be > 10.

3. Final Answer:

   false -> Option C

4. Quick Check:

   6 in right subtree < 10 breaks BST = false [OK]

Hint: Check if left < node < right recursively [OK]

Common Mistakes:

• Ignoring subtree value constraints
• Assuming all children just compare with parent
• Missing base case for null nodes

4. Find the bug in this BST validation function and select the fix:

function isBST(node) {
  if (!node) return true;
  if (node.left && node.left.val >= node.val) return false;
  if (node.right && node.right.val <= node.val) return false;
  return isBST(node.left) && isBST(node.right);
}

medium

A. Add min and max parameters to track value ranges

B. Change >= to > and <= to < in comparisons

C. Return false if node is null

D. Remove recursive calls to isBST

Solution

1. Step 1: Understand current checks

   Function only compares immediate children with current node, missing subtree constraints.

2. Step 2: Identify fix

   To correctly validate BST, function must track allowed min and max values for each subtree, not just immediate children.

3. Final Answer:

   Add min and max parameters to track value ranges -> Option A

4. Quick Check:

   Use min/max limits to validate BST correctly [OK]

Hint: Use min/max limits, not just immediate child values [OK]

Common Mistakes:

• Only checking immediate children
• Ignoring subtree value constraints
• Not using recursion properly

5. Given a binary tree where nodes can have duplicate values, which modification to the BST validation logic allows duplicates only on the right subtree? Choose the correct condition to replace node.val <= min and node.val >= max checks in the recursive function.

hard

A. Allow duplicates by changing left subtree check to node.val < min and right subtree check to node.val > max

B. Allow duplicates on right by changing left subtree check to node.val <= min and right subtree check to node.val > max

C. Allow duplicates on right by changing left subtree check to node.val <= min and right subtree check to node.val >= max

D. Allow duplicates on right by changing left subtree check to node.val < min and right subtree check to node.val >= max

Solution

1. Step 1: Understand duplicates in BST

   Allowing duplicates only on right means left subtree nodes must be strictly less than current node, right subtree nodes can be greater or equal.

2. Step 2: Adjust min/max checks accordingly

   Left subtree check should be node.val < min (strictly less), right subtree check should be node.val >= max (allow equal).

3. Final Answer:

   Allow duplicates on right by changing left subtree check to node.val < min and right subtree check to node.val >= max -> Option D

4. Quick Check:

   Duplicates only right: left < node, right >= node [OK]

Hint: Strict less on left, allow equal on right for duplicates [OK]

Common Mistakes:

• Allowing duplicates on both sides
• Using non-strict inequalities on left subtree
• Confusing min and max checks