Why Validate if Tree is BST in DSA Go?

The Big Idea

Discover the simple trick that saves hours of confusing tree checks!

The Scenario

Imagine you have a family tree drawn on paper. You want to check if the tree follows a special rule: every child on the left is smaller than the parent, and every child on the right is bigger. Doing this by looking at each node and comparing with all others is tiring and confusing.

The Problem

Manually checking each node against all others takes a lot of time and is easy to mess up. You might forget to check some nodes or compare in the wrong order. This makes the process slow and error-prone, especially for big trees.

The Solution

Using a smart method, we can check the tree by walking through it once, keeping track of allowed value ranges for each node. This way, we quickly confirm if the tree follows the rule without extra work or mistakes.

Before vs After

✗ Before

func isBSTManual(root *Node) bool {
    if root == nil {
        return true
    }
    if !checkAllNodes(root.Left, root.Value, true) || !checkAllNodes(root.Right, root.Value, false) {
        return false
    }
    return isBSTManual(root.Left) && isBSTManual(root.Right)
}

✓ After

func isBST(root *Node, min, max *int) bool {
    if root == nil {
        return true
    }
    if (min != nil && root.Value <= *min) || (max != nil && root.Value >= *max) {
        return false
    }
    return isBST(root.Left, min, &root.Value) && isBST(root.Right, &root.Value, max)
}

What It Enables

This method lets us quickly and correctly check if any tree is a valid Binary Search Tree, even if it is very large.

Real Life Example

When building a phone contact list that must stay sorted for fast search, we use this check to ensure the data structure is correct and efficient.

Key Takeaways

Manual checking is slow and error-prone.

Using value ranges during traversal simplifies validation.

This method works efficiently for any tree size.

Practice

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

easy

A. All nodes have the same value.

B. Every node has exactly two children.

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

D. Every node's left subtree contains values less than the node, and right subtree contains values greater.

Solution

1. Step 1: Understand BST property

   A BST requires that for each node, all values in the left subtree are less than the node's value, and all values in the right subtree are greater.

2. Step 2: Compare options with definition

   Every node's left subtree contains values less than the node, and right subtree contains values greater. matches the BST property exactly, while others describe different tree properties.

3. Final Answer:

   Every node's left subtree contains values less than the node, and right subtree contains values greater. -> Option D

4. Quick Check:

   BST property = Every node's left subtree contains values less than the node, and right subtree contains values greater. [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 Go function signature correctly represents a function to check if a binary tree is a BST?

easy

A. func isBST(root *Node) bool

B. func isBST(root Node) int

C. func checkBST(root *Node) string

D. func validateBST(root Node) void

Solution

1. Step 1: Identify correct parameter and return types

   The function should accept a pointer to the root node (to avoid copying) and return a boolean indicating if the tree is BST.

2. Step 2: Match with options

   func isBST(root *Node) bool matches this: it takes *Node and returns bool. Others have wrong parameter types or return types.

3. Final Answer:

   func isBST(root *Node) bool -> Option A

4. Quick Check:

   Pointer input + bool output = func isBST(root *Node) bool [OK]

Hint: Use pointer receiver and bool return for BST check [OK]

Common Mistakes:

• Passing Node by value instead of pointer
• Returning int or string instead of bool
• Using void (no return) for validation function

3. Given the following Go code, what will be the output?

package main

import "fmt"

type Node struct {
    Val   int
    Left  *Node
    Right *Node
}

func isBSTUtil(node *Node, min, max int) bool {
    if node == nil {
        return true
    }
    if node.Val <= min || node.Val >= max {
        return false
    }
    return isBSTUtil(node.Left, min, node.Val) && isBSTUtil(node.Right, node.Val, max)
}

func isBST(root *Node) bool {
    return isBSTUtil(root, -1000, 1000)
}

func main() {
    root := &Node{Val: 10}
    root.Left = &Node{Val: 5}
    root.Right = &Node{Val: 15}
    root.Right.Left = &Node{Val: 6}
    root.Right.Right = &Node{Val: 20}
    fmt.Println(isBST(root))
}

medium

A. false

B. true

C. Compilation error

D. Runtime panic

Solution

1. Step 1: Trace tree values against BST rules

   The node with value 6 is in the right subtree of 10 but less than 10, violating BST property.

2. Step 2: Check isBSTUtil logic

   isBSTUtil checks if node.Val is within (min, max). For node 6, min=10, max=15, but 6 <= 10 fails the condition, returning false.

3. Final Answer:

   false -> Option A

4. Quick Check:

   6 in right subtree < 10 = false [OK]

Hint: Check subtree values against min/max bounds [OK]

Common Mistakes:

• Ignoring subtree value constraints
• Assuming all nodes in right subtree are greater than root only
• Not updating min/max bounds during recursion

4. The following Go function is intended to check if a binary tree is a BST, but it has a bug. What is the bug?

func isBST(node *Node) bool {
    if node == nil {
        return true
    }
    if node.Left != nil && node.Left.Val > node.Val {
        return false
    }
    if node.Right != nil && node.Right.Val < node.Val {
        return false
    }
    return isBST(node.Left) && isBST(node.Right)
}

medium

A. It does not handle nil nodes correctly.

B. It only compares immediate children, missing deeper subtree violations.

C. It uses wrong comparison operators for BST.

D. It causes infinite recursion.

Solution

1. Step 1: Analyze comparison logic

   The function compares only node.Left.Val and node.Right.Val with node.Val, ignoring entire subtree values.

2. Step 2: Understand BST violation cases

   A violation can occur deeper in subtrees, e.g., a left subtree node greater than root, which this function misses.

3. Final Answer:

   It only compares immediate children, missing deeper subtree violations. -> Option B

4. Quick Check:

   Check all subtree nodes, not just immediate children [OK]

Hint: Check entire subtree ranges, not just direct children [OK]

Common Mistakes:

• Checking only immediate children values
• Not passing min/max bounds in recursion
• Assuming local checks guarantee global BST

5. You want to validate if a binary tree is a BST but the tree nodes can have duplicate values. Which modification to the standard BST validation logic is correct to allow duplicates only on the right subtree?

hard

A. Change the condition to allow node.Val <= max for left subtree and node.Val > max for right subtree.

B. Allow duplicates only if node.Val >= min for left subtree and node.Val < max for right subtree.

C. Allow duplicates only if node.Val > min for left subtree and node.Val <= max for right subtree.

D. Allow duplicates on both sides without changing conditions.

Solution

1. Step 1: Understand duplicate placement in BST

   Duplicates allowed only on right means left subtree nodes must be strictly less than node.Val, right subtree nodes can be equal or greater.

2. Step 2: Adjust min/max conditions accordingly

   Change violation check to (node.Val <= min || node.Val > max), enforcing node.Val > min && node.Val <= max. This allows equality to max (parent.Val in right calls) but enforces > min (parent.Val in left calls).

3. Final Answer:

   Allow duplicates only if node.Val > min for left subtree and node.Val <= max for right subtree. -> Option C

4. Quick Check:

   > min && <= max = duplicates on right only [OK]

Hint: Use > min && <= max to allow duplicates on right [OK]

Common Mistakes:

• Allowing duplicates on left subtree
• Not adjusting inequality signs properly
• Allowing duplicates on both sides without rules