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<div class="alert alert-note">
<h1>
Binary Search Tree Implementation
</h1>
<p>
A binary tree in which for each node, value of all the nodes in the left subtree is lesser or equal and value of all the nodes in the right subtree is greater than the root node.
<br>
<img src="https://i.imgur.com/DYkRBqz.png">
</p>
<p>
<h3>Height of the Tree</h3>
<li> Height of the leaf node is 0 </l>
<li> Height of an empty tree is -1 </l>
<li> Height is number of edges from root node to the given node.</l>
<li> Height of the root node is the height of the tree. </li>
<p>
<img src="https://i.imgur.com/7D2w9IC.png" alt="BST height">
</p>
</p>
<p>
<b> Heap</b> is a dynamic memory.
Local variables of functions are stored in <b> Stack</b>. Whenever a function finishes the stack frame is reclaimed.
</p>
<p>
<h3>Search</h3>
<p>
<h4>Recursive Search</h4>
Time Complexity: O(log (n)), Space Complexity: O(log (n))
</p>
<p>
<h4>Iterative Search</h4>
Time Complexity: O(log (n)), Space Complexity: O(1)
</p>
</p>
<p>
<h3>
Insert
</h3>
<b>
O(Log(n)) time | Space O(h) where h is the height of the tree
</b><br>
For 1 insert operation, avg case is O(lgn) and worst case is O(n) <br>
For n insert operations, avg case is O(nlgn) and worst case is O(n^2)
</p>
<p>
<h3>
Delete
</h3>
<b>
O(Log(n)) time | Space O(h) where h is the height of the tree
</b><br>
<li>
<strong>Case 1: No child</strong>
</li>
<li>
<strong>Case 2: One child</strong>
</li>
<li>
<strong>Case 3: Two child</strong>
Find Minimum in the right subtree copy the value in the targeted node. Delete the duplicate from right-subtree.
</li>
<br>
<img src="https://i.imgur.com/VuruDcG.png" alt="delete node in bst">
</p>
</div>
.alert {
padding: 20px;
border-radius: 25px;
margin-bottom: 15px;
}
.alert-tip {
background-color: #def6dd;
}
.alert-note {
background-color: #efd9fd;
overflow-x: auto;
}
pre {
overflow-x: auto;
white-space: pre-wrap;
white-space: -moz-pre-wrap;
white-space: -pre-wrap;
white-space: -o-pre-wrap;
word-wrap: break-word;
}
/*
Nodes are created in the heap seciton of the memory
Address of the root node we keep for a tree.
*/
class Node {
constructor(data) {
this.data = data;
this.left = null;
this.right = null;
}
}
/*
O(Log(n)) time | Space O(h) where h is the height of the tree
For 1 insert operation, avg case is O(lgn) and worst case is O(n)
For n insert operations, avg case is O(nlgn) and worst case is O(n^2)
*/
function insertRecursively(root, data) {
// If the tree is empty create new node.
if (root == null) root = new Node(data);
else if (data <= root.data) root.left = insert(root.left, data);
else root.right = insert(root.right, data);
return root;
}
/*
O(Log(n)) time | Space O(1)
For 1 insert operation, avg case is O(log(n)) and worst case is O(n)
For n insert operations, avg case is O(nlgn) and worst case is O(n^2)
*/
function insert(root, data) {
const nodeToInsert = new Node(data);
if (root == null) return nodeToInsert;
let current = root;
let previous = root;
while (current != null) {
previous = current;
if (data <= current.data) current = current.left;
else current = current.right;
}
if (data <= previous.data) previous.left = nodeToInsert;
else previous.right = nodeToInsert;
return root;
}
// O(log n) time | space O(1)
function remove(root, data) {
if (root == null) return root;
else if (data < root.data) root.left = remove(root.left, data);
else if (data > root.data) root.right = remove(root.right, data);
else {
// found the node.
// case 1: no child
if (root.left == null && root.right == null) {
root = null;
} else if (root.left == null) {
// case 2: One child
let current = root;
root = root.right;
current = null;
} else if (root.right == null) {
let current = root;
root = root.left;
current = null;
} else {
// case 3: Two child
let current = findMin(root.right);
root.data = current.data;
root.right = remove(root.right, current.data);
}
}
return root;
}
// O(log(n)) time | O(log (n))
function searchRecursive(root, data) {
if (root == null) return false;
else if (data === root.data) return true;
else if (data <= root.data) return search(root.left, data);
else return search(root.right, data);
}
// O(log(n)) time | O(log (n))
function search(root, data) {
while (root != null) {
if (data === root.data) return true;
else if (data <= root.data) root = root.left;
else root = root.right;
}
return false;
}
function findMin(root) {
if (root == null) return root;
while (root.left) {
root = root.left;
}
return root.data;
}
function findMax(root) {
if (root == null) return root;
while (root.right) {
root = root.right;
}
return root.data;
}
// O(n) time | (O log(n)) space
function findHeight(root) {
if (root == null) return -1; // empty tree height is -1
return Math.max(findHeight(root.left), findHeight(root.right)) + 1;
}
describe("In Binary Search Tree", () => {
it("I can insert", () => {
let root = null;
root = insert(root, 15);
root = insert(root, 10);
root = insert(root, 20);
root = insert(root, 25);
root = insert(root, 8);
root = insert(root, 12);
expect(root).toBeTruthy();
});
it("I can insert recursively", () => {
let root = null;
root = insertRecursively(root, 15);
root = insertRecursively(root, 10);
root = insertRecursively(root, 20);
root = insertRecursively(root, 25);
root = insertRecursively(root, 8);
root = insertRecursively(root, 12);
expect(root).toBeTruthy();
});
});
describe("I can perform below operations in BST", () => {
let root = null;
beforeEach(() => {
root = null;
root = insert(root, 15);
root = insert(root, 10);
root = insert(root, 20);
root = insert(root, 25);
root = insert(root, 8);
root = insert(root, 12);
});
it("I can search recursively", () => {
expect(searchRecursive(root, 8)).toBeTruthy();
expect(searchRecursive(root, 22)).toBeFalsy();
});
it("I can search iteratively", () => {
expect(search(root, 8)).toBeTruthy();
expect(search(root, 22)).toBeFalsy();
});
it("I can find Minimum in BST", () => {
expect(findMin(root)).toBe(8);
});
it("I can find Maximum in BST", () => {
expect(findMax(root)).toBe(25);
});
it("I can find Height of BST", () => {
expect(findHeight(root)).toBe(2);
});
it("I can find Delete 8 from BST", () => {
remove(root, 8);
expect(search(root, 8)).toBeFalsy();
});
});
Also see: Tab Triggers