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Java DSA Quick Revision

A beginner-friendly and intermediate-level Data Structures and Algorithms repository implemented in Java for quick revision, concept learning, and interview preparation.

This repository contains clean and well-structured implementations of core DSA concepts with:

  • Step-by-step comments
  • Separate Driver classes
  • Time & Space Complexity analysis
  • Beginner-friendly code structure
  • Easy-to-understand implementations

Perfect for:

  • Placement preparation
  • DSA revision
  • Java practice
  • Interview preparation

Repository Structure

Beginner Level

Array

Matrix

Search

Sort

Stack

Queue

LinkedList

Recursion

Bit Manipulation

Hashing


Intermediate Level

Tree

Graph

Dynamic Programming

Backtracking

Features

  • Clean Java implementations
  • Beginner-friendly coding style
  • Separate Driver files for execution
  • Detailed comments for understanding
  • Quick revision focused
  • Covers basic to intermediate DSA
  • Simple project structure

Technologies Used

  • Java
  • VS Code
  • Object-Oriented Programming (OOP)

How to Run

Clone Repository

git clone https://github.com/Nikit-370/Java-DSA-Quick-Revision.git

Open Project

Open the project in:

  • IntelliJ IDEA
  • Eclipse
  • VS Code

Compile and Run

javac Driver.java
java Driver

Learning Goals

This repository is created for:

  • Strengthening DSA fundamentals
  • Quick interview revision
  • Improving problem-solving concepts
  • Understanding core data structures visually through code

Author

Nikit Singh Kanyal

  • MCA Student
  • Java & DSA Learner
  • Cloud & Software Enthusiast

GitHub: Nikit-370


Support

If you found this repository helpful, consider giving it a ⭐ on GitHub.

Happy Coding 🚀

About

A beginner-friendly Java DSA repository for quick revision and concept learning. Includes step-by-step implementations of Arrays, Linked Lists, Stack, Queue, Trees, Graphs, Dynamic Programming, Recursion, Hashing, Backtracking, Sorting, Searching, Bit Manipulation, and more with separate driver programs and time complexity analysis.

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