Learn Data Structures with Javascript | DSA using JavaScript Tutorial

JavaScript (JS) is the most popular lightweight, interpreted programming language, and might be your first preference for Client-side as well as Server-side developments. But have you thought about using JavaScript for DSA? Learning Data Structures and Algorithms can be difficult when combined with JavaScript. For this reason, we have brought to you this detailed DSA tutorial on how to get started with Data Structures with JavaScript from scratch.

Data Structures with JavaScript

How to start learning Data Structures with JavaScript?

The first and foremost thing is dividing the total procedure into little pieces which need to be done sequentially.

The complete process to learn DS from scratch can be broken into 3 parts.

1. Learn about Time and Space complexities
2. Learn the basics of individual Data Structures
3. Practice Problems on Data Structures

1. Learn about Complexities

Here comes one of the interesting and important topics. The primary motive to use DSA is to solve a problem effectively and efficiently. How can you decide if a program written by you is efficient or not? This is measured by complexities. Complexity is of two types.

1. Time Complexity: Time complexity is used to measure the growth of execution time of an algorithm as the size of the input increases.
2. Space Complexity: Space complexity refers to the amount of memory required by an algorithm as a function of the size of the input. 
   You will also come across the term Auxiliary Space very commonly in DSA, which refers to the extra space used in the program other than the input data structure.

2. Learn Data Structures

Here comes the most crucial and the most awaited stage of the roadmap for learning data structure and algorithm – the stage where you start learning about DSA. The topic of DSA consists of two parts: 

• Data Structures
• Algorithms 

Though they are two different things, they are highly interrelated, and it is very important to follow the right track to learn them most efficiently. If you are confused about which one to learn first, we recommend you to go through our detailed analysis on the topic: What should I learn first- Data Structures or Algorithms?

Here we have followed the flow of learning a data structure and then the most related and important algorithms used by that data structure.

1. Array in JavaScript

The array is a data structure that allows you to store multiple values in a single variable. Arrays are used to hold collections of data, and each value in an array is called an element. Arrays can store elements of any data type, including numbers, strings, objects, and even other arrays.

• Array Data Structure Guide in JavaScript
• Practice Problems on Arrays in JavaScript
• Top Array Problem Interviews in JavaScript

2. String in JavaScript

A string is a sequence of characters used to represent text. Strings are primitive data types but can also be treated as objects when using methods and properties. Strings are immutable, meaning once a string is created, it cannot be changed.

• Guide on Strings in JavaScript
• Practice Problems on String in JavaScript
• JavaScript String Interview Questions

3.  Linked List in JavaScript

A linked list in JavaScript is a linear data structure where each element (called a node) contains data and a reference (or pointer) to the next node in the sequence. Unlike arrays, linked lists do not have indexed access, and elements are dynamically allocated in memory.

• Linked List Data Structure Guide in JavaScript
• Top 50 Problems on Linked List for Interviews

4. Searching Algorithms

Searching algorithms in JavaScript help find elements in datasets. Linear Search checks each element sequentially, while Binary Search divides the array in half for faster searches in sorted data. Jump Search jumps ahead in blocks, and Interpolation Search estimates positions based on value distribution. Each algorithm offers varying levels of efficiency depending on the dataset’s structure.

• Guide on Searching Algorithms in JavaScript
• Practice Problems on Searching in JavaScript

5. Sorting Algorithm

Sorting algorithms in JavaScript arrange data in a specific order. Bubble Sort, Selection Sort, and Insertion Sort are simple comparison-based algorithms, while Merge Sort and Quick Sort are more efficient, using divide-and-conquer strategies.

• Guide on Sorting Algorithms in JavaScript
• Practice Problems on Sorting in JavaScript
• Top Problems on Sorting in JavaScript

6. Hash

A hash in JavaScript is a data structure that stores key-value pairs for fast retrieval. Hash functions convert keys into fixed-size values, allowing quick access. Hashing is commonly used in dictionaries, caches, and databases for efficient data operations.

• Guide on Hashing in JavaScript
• Hashing based Interview Questions in JS

7. Two Pointer

The Two Pointer technique in JavaScript uses two pointers to traverse a data structure, typically an array, at different speeds or positions. This method is often applied to problems like finding pairs, checking for specific conditions, or merging sorted arrays.

• Guide on Two Pointer in JavaScript

8. Recursion

Recursion in JavaScript is a technique where a function calls itself to solve a problem by breaking it into smaller subproblems of the same type. Every recursive function must have a base case, which stops the recursion, and a recursive case, where the function calls itself with a smaller input.

• Guide on Recursion in JavaScript
• Recursion Practice Problems
• Top 50 Problem on Recursion

9. Stack in JavaScript

A stack is a data structure that follows the Last In, First Out (LIFO) principle. This means that the last element added to the stack will be the first one to be removed. Stacks are commonly used for managing function calls, tracking history (e.g., undo operations), and parsing expressions

• Stack Guide in JavaScript
• Top 50 problems on Stack for Interview in JavaScript

10. Queue in JavaScript

A Queue in JavaScript is a linear data structure that follows the FIFO (First In, First Out) principle, where elements are added at the end and removed from the front. It can be implemented using an array with push() for enqueue and shift() for dequeue operations.

• Queue Guide in JavaScript
• Top 50 problems on Queue for Interview in JS

11. Tree in JavaScript

A Tree in JavaScript is a hierarchical data structure where each node has a value and references to child nodes. It is commonly used for representing hierarchical relationships like the DOM, file systems, or organizational structures.

• Tree Guide in JavaScript
• Types in Tree Data Structure
• Top 50 Tree Coding Problems in JavaScript

12. Priority Queue in JavaScript

A Priority Queue in JavaScript is a special type of queue where elements are dequeued based on priority rather than the order they were added. It can be implemented using a heap (binary heap for efficiency) or an array with sorting.

• Priority Queue Guide in JavaScript

13. Map in JavaScript

A Map in JavaScript is a collection of key-value pairs where keys can be of any data type. It maintains the insertion order and provides efficient methods for adding, deleting, and retrieving values.

• Map Guide in JavaScript

14.  Set in JavaScript

A Set in JavaScript is a collection of unique values, meaning it does not allow duplicate entries. It provides methods to add, delete, and check the existence of elements efficiently.

• Set Guide in JavaScript

15. Graph in JavaScript

A Graph in JavaScript is a data structure consisting of nodes (vertices) connected by edges. It can be represented using an adjacency list or an adjacency matrix and is used for modeling networks, relationships, and paths. 

• Graph Guide in JavaScript
• Top 50 Graph Coding Problems in JavaScript
• Graph Representation in JavaScript

3. Built-in Data Structures in JavaScript

Let’s see what inbuilt data structures JavaScript offers us:

4. Practice Problems on Data Structures and Algorithms (DSA)

For practicing problems on individual data structures and algorithms, you can use the following links: 

• Practice problems on Arrays
• Practice problems on Strings
• Practice problems on Linked Lists
• Practice problems on Stack
• Practice problems on Queue
• Practice problems on Tree
• Practice problems on Graph
• Practice problems on Sorting algorithm
• Practice problems on Searching algorithm
• Practice problems on Greedy algorithm
• Practice problems on Divide And Conquer algorithm
• Practice problems on Recursion algorithm
• Practice problems on Backtracking algorithm
• Practice problems on Dynamic Programming algorithm

Apart from these, there are many other practice problems that you can refer based on their respective difficulties: 

• School-level
• Basic level
• Easy level
• Medium level
• Hard level

You can also try to solve the most asked interview questions based on the list curated by us at: 

• Must-Do Coding Questions for Companies
• Top 50 Array Coding Problems for Interviews
• Top 50 String Coding Problems for Interviews
• Top 50 Tree Coding Problems for Interviews
• Top 50 Dynamic Programming Coding Problems for Interviews

You can also try our curated lists of problems below articles:

• SDE SHEET – A Complete Guide for SDE Preparation
• DSA Sheet by Love Babbar