🧠 JavaScript Data Structures & Algorithms

A Practical Implementation Guide for Modern JavaScript

📖 Overview

Welcome to a comprehensive collection of Data Structures and Algorithms implemented in JavaScript. This repository is designed to help developers, students, and coding enthusiasts understand fundamental computer science concepts through practical JavaScript implementations.

From basic Big O notation analysis to complex dynamic programming problems, each topic includes clean, well-documented code that you can run, modify, and learn from.

🗂️ Repository Structure

📁 JavaScript_DataStructure-Algorithm/
│
├── 📁 BIG_O_Notation/              # Time & Space Complexity Analysis
├── 📁 3. Analyzing Performance of Arrays and Objects/
├── 📁 Problem_Solving_Approach/    # Systematic Problem-Solving Techniques
├── 📁 Recursion/                   # Recursive Algorithms
├── 📁 Searching_Algorithm/         # Various Search Algorithms
├── 📁 Sorting/                     # Sorting Algorithms (Radix Sort, etc.)
│
├── 📁 class/                       # JavaScript Class Implementations
├── 📁 SingleLinkList/              # Singly Linked Lists
├── 📁 DoubleLinkList/              # Doubly Linked Lists
├── 📁 stack/                       # Stack Implementation (Using Linked List)
├── 📁 Queue/                       # Queue Implementation
│
├── 📁 tree/                        # Tree Data Structures
├── 📁 Heap/                        # Heap Data Structure
├── 📁 HashFunction/                # Hash Tables & Functions
├── 📁 Graph/                       # Graph Algorithms (Dijkstra's, etc.)
├── 📁 Dynamic_Programing/          # Dynamic Programming Problems
│
├── 📄 .gitignore                   # Git ignore file
├── 📄 LICENSE                      # MIT License
└── 📄 README.md                    # This documentation

📚 Topics Covered

Foundational Concepts

• Big O Notation: Understanding time and space complexity
• Performance Analysis: Arrays vs Objects performance characteristics
• Problem Solving Approaches: Systematic methodologies for tackling algorithms

Core Data Structures

• Linked Lists: Singly and Doubly Linked Lists
• Stacks & Queues: Implementations using linked lists
• Trees: Various tree data structures
• Heaps: Priority queue implementations
• Hash Tables: Hash functions and collision handling
• Graphs: Graph representations and algorithms

Essential Algorithms

• Recursion: Understanding and implementing recursive solutions
• Searching Algorithms: Different search techniques
• Sorting Algorithms: Multiple sorting approaches including Radix Sort
• Graph Algorithms: Dijkstra's algorithm and others
• Dynamic Programming: Solving complex problems with optimal substructure

🚀 Getting Started

Prerequisites

• Node.js (version 12 or higher recommended)
• Basic understanding of JavaScript (ES6+)
• Familiarity with programming concepts

Running the Code

Each folder contains standalone JavaScript files that you can execute:

# Navigate to a specific topic
cd Sorting

# Run a JavaScript file using Node.js
node radixSort.js

For Development

# Clone this repository
git clone https://github.com/Feroz455/JavaScript_DataStructure-Algorithm.git

# Navigate to the repository
cd JavaScript_DataStructure-Algorithm

# Explore different topics
ls -la

💡 Learning Path

Beginner Level (Week 1-2)

1. Start with BIG_O_Notation to understand algorithm efficiency
2. Move to Problem_Solving_Approach for systematic thinking
3. Practice Recursion with simple examples
4. Implement basic Searching_Algorithm

Intermediate Level (Week 3-4)

1. Master Linked Lists (Single and Double)
2. Implement Stacks and Queues
3. Study Sorting algorithms
4. Explore Tree data structures

Advanced Level (Week 5-6)

1. Dive into Graph algorithms
2. Solve Dynamic Programming problems
3. Implement Heap and Hash Tables
4. Analyze complex algorithm performance

🧪 Code Examples

Each implementation follows consistent patterns:

// Example structure from linked list implementation
class Node {
    constructor(value) {
        this.value = value;
        this.next = null;
        this.prev = null; // For doubly linked lists
    }
}

class LinkedList {
    constructor() {
        this.head = null;
        this.tail = null;
        this.length = 0;
    }
    
    // Various methods: push, pop, shift, unshift, get, set, insert, remove
}

📊 Repository Statistics

Metric	Value	Details
Total Topics	15+	Comprehensive coverage
Primary Language	100% JavaScript	ES6+ implementations
Total Commits	32	Active development
Initial Commit	November 20, 2022	Project start
Last Update	December 29, 2025	Recent maintenance
License	MIT	Open source

🎯 Key Features

• Clean Code: Well-structured, readable implementations
• Practical Examples: Real-world applicable code
• ES6+ Syntax: Modern JavaScript features
• Modular Design: Each topic in its own directory
• Educational Focus: Code is commented for learning

🤝 How to Contribute

Contributions that improve code quality, add more examples, or enhance documentation are welcome!

Contribution Guidelines:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/improvement)
3. Commit your changes (git commit -m 'Add: description of improvement')
4. Push to the branch (git push origin feature/improvement)
5. Open a Pull Request

Areas for Improvement:

• Adding more algorithm implementations
• Improving code comments and explanations
• Adding test cases
• Enhancing performance optimizations
• Adding visualizations or diagrams

📄 License

This project is licensed under the MIT License. See the LICENSE file for full details. This is a permissive license, allowing use for both personal and commercial purposes.

🔗 Related Resources

Online Learning Platforms

• LeetCode - Practice coding problems
• freeCodeCamp - Free coding curriculum
• MDN Web Docs - JavaScript reference

Recommended Books

• "JavaScript Data Structures and Algorithms" by Sammie Bae
• "Eloquent JavaScript" by Marijn Haverbeke
• "Introduction to Algorithms" by Cormen et al.

Useful Tools

• VisuAlgo - Algorithm visualizations
• Big-O Cheat Sheet - Complexity reference

🙏 Acknowledgments

This repository is built on the collective knowledge of computer science education and the JavaScript developer community. Special thanks to all algorithm educators and open-source contributors who make learning accessible to everyone.

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💻 "The best way to understand an algorithm is to implement it."

Happy Coding & Algorithm Learning! 🚀

Maintained by Feroz455 | Last Updated: December 2025