DSA Blind 75 | Problems and solutions

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75 DSA problems topicwise

Given below is a list of popular DSA problems topicwise with solutions.
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Finding Height Of A Binary Tree

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Height of a Binary tree is the length of the path form its root node to its farthest leaf node or we can say the longest path from root node to any of the leaf node (here path means the link between two nodes). For example - height of the binary tree in the figure given below (Fig 1.0) is 3. As we can see that this tree has two leaf nodes 3 and 12 but node leaf 3 is the farthest from the root and length of the path between 10 (root node) and 3 (farthest leaf node) is 3 hence height of the tree is 3. From above example comes our algorithm to calculate the height of the tree, we will calculate the height of the left and right subtree of each node recursively and consider the height of the tree including the root node - adding one to the greater of the two heights (left and right subtree heights). Fig 1.0 Implementation - In below code we have implementaed a custom BST with a public method getHeight() which internaly calls another private method getHeight() passing root of the tree ...
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DSA Array | Valid Anagram

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Problem Statement Write a function that takes two strings, s and t, as input and determines whether they are anagrams of each other. Return true if the two strings are anagrams and false otherwise. An anagram is defined as a string formed by rearranging the characters of another string, using all the original characters exactly once. Example 1: Input: s = "listen", t = "silent" Output: true Explanation: Both strings contain the same characters ('l', 'i', 's', 't', 'e', 'n') in different orders. Example 2: Input: s = "hello", t = "world" Output: false Explanation: The characters in s and t do not match exactly. Code: class Solution { public boolean isAnagram(String s, String t) { Map <Character, Integer> map = new HashMap <> (); int n1 = s.length(); ...
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Binary Search Tree Insertion Recursive Approach

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In this article we will see how we can write the insert method for a binary tree using recursive approach. We have already covered the iterative approach in this article -  Binary Search Tree Insertion Iterative Approach  with some basic details about binary search tree data structure. package ds.tree; public class BStree { private Node root; public BStree(int rootData) { this.root = new Node(rootData); } static class Node { int data; Node left; Node right; public Node(int data) { this.data = data; } } public void insertRecursive(int data) { insertRec(this.root, data); } private Node insertRec(Node root, int data) { if(root == null) return new Node(data); if(root.data &lt data) root.right = insertRec(root.right, data); else root.left = insertRec(root.left, data); return root; } public void printTree() { System.out.print(root.data + ", " + root.left.data + ", " + root.right.data); } } Notice that ...
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Find nth Smallest Element In Binary Search Tree

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In the continuation of Binary Search Tree articles here comes another exciting one. In this article we will see how we can find the nth smallest element in a Binary Search Tree. Let's take the example of binary search tree given in the figure below (Fig 1.0) and see how to find its 3rd smallest element. Fig 1.0 Explanation - One thing we know for sure that we will have to traverse through this tree if we want to find any element, if so then what could be better than In-Order Traversal in this case because it gives us the nodes in ascending order. Now once we know how to traverse in ascending order only thing left is to take a counter to check whether we have traversed the n (3 in this example) nodes. Once the counter reach the value n we know its our nth smallest element. We will use the similar approach in the implementation give below, we will traverse the tree using In-Order traversal and take a counter to check the number of nodes we have traversed and as soon as the counter...
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