Data structures and algorithms

Learn data structures through practical coding problems.

Build stronger problem-solving skills with tutorials on arrays, linked lists, stacks, trees, binary search trees, heaps, and priority queues.

Practice library

47

lessons

19

linear

28

non-linear

What is a data structure?

A data structure is a way of organizing data in the computer's memory so that it can be used effectively and efficiently. For learners, it helps to first separate data structures into two main types: linear data structures and non-linear data structures.

Linear data structures

  1. Array
  2. Linked List
  3. Stack
  4. Queue

Non-linear data structures

  1. Tree
  2. Graph List

Topic-wise learning

Choose a data structure

Start with linear structures, then move into trees and heaps when you are ready for hierarchical and priority-based problems.

Linear data structures

Learn structures where data is arranged one after another.

Array5Linked List5Stack9
QueueComing later

Non-linear data structures

Learn structures where data is connected through relationships.

Tree21Binary Tree16Binary Search Tree4Heap and Priority Queue7
Graph ListComing later

Programs by hierarchy

Data structure programs for learners

Follow the same hierarchy used in the introduction. Start with linear data structures, then move into tree-based and heap-based non-linear topics.

Array

Array programs cover contiguous storage, indexes, traversal, searching, rotation, and pair-based problems.

5 programs
  1. 1Introduction to Arrays
  2. 2Reverse elements of an array
  3. 3Second largest element in an array
  4. 4Left rotation of an array
  5. 5Pair with given sum in an array

Linked List

Linked list programs focus on node connections, traversal, insertion, middle-node lookup, and reversing a list.

5 programs
  1. 1Introduction to Linked list
  2. 2Linked List
  3. 3Doubly Linked List
  4. 4Program to find middle element of a Linked List
  5. 5Program to reverse a linked list

Stack

Stack programs build LIFO problem-solving skills for nearest-element, histogram, span, and bracket-matching problems.

9 programs
  1. 1Stack using array
  2. 2Stack using linked list
  3. 3Nearest greater to right
  4. 4Nearest greater to left
  5. 5Nearest smaller to right
  6. 6Nearest smaller to left
  7. 7Stock span problem
  8. 8Maximum area histogram
  9. 9Balanced brackets problem

Tree

Tree is a non-linear data structure. Start with the basic tree introduction, then continue into Binary Tree and Binary Search Tree as nested topics.

21 programs
  1. 1Introduction to Trees

Binary Tree

Binary tree programs cover traversal, search, height, size, leaf nodes, full and half nodes, diameter, and paths.

16 programs
  1. 1Introduction to Binary Tree
  2. 2Binary tree traversals
  3. 3Reverse level order traversal
  4. 4Maximum in Binary tree
  5. 5Search a node in Binary tree
  6. 6Size of a binary tree
  7. 7Height of a binary tree
  8. 8Deepest node in a binary tree
  9. 9Number of leaf nodes in a binary tree
  10. 10Number of full nodes in a binary tree
  11. 11Number of half nodes in a binary tree
  12. 12Compare structure of two binary trees
  13. 13Compare structure and data of two binary trees
  14. 14Maximum level sum in a binary tree
  15. 15Diameter of a Binary tree
  16. 16All root-to-leaf paths of a Binary tree

Binary Search Tree

Binary search tree programs focus on ordered lookup, minimum-value search, and insertion.

4 programs
  1. 1Introduction to Binary Search Tree
  2. 2Search a node in Binary search tree
  3. 3Search the node with minimum value in a Binary search tree
  4. 4Insertion in Binary Search Tree

Heap and Priority Queue

Heap programs cover min heap, max heap, heapify, heapsort, built-in heap usage, and priority queues.

7 programs
  1. 1Heap
  2. 2Min heap
  3. 3Max heap
  4. 4Heapify
  5. 5Heap sort
  6. 6Built-in Heaps
  7. 7Priority Queue