Algorithmic-Implementations-in-Java

A collection of Java-based data structure and algorithm implementations. Each folder in this repository contains a standalone problem solution focusing on different core computer science concepts such as data structures, trees, linked lists, and compression algorithms.

⚡ 1. HuffmanCompression

Folder: HuffmanCompression/
Main Concepts: Frequency mapping, priority lists, Huffman trees, file encoding/decoding
Core Classes: HuffmanList, HuffmanNode, HuffmanTree, Main

🧩 Overview

This implementation demonstrates the Huffman Coding Algorithm, a core data compression technique used to minimize storage by assigning shorter codes to more frequent symbols.

🔍 Features

• Converts text files into symbol-frequency mappings
• Builds a sorted Huffman linked list and binary tree
• Encodes text using Huffman codes
• Decodes the encoded text back into the original form
• Handles file I/O operations (read/write) for encoded and decoded data

🧠 How It Works

1. Reads input from source.txt
2. Calculates frequency of each character
3. Builds a Huffman Tree
4. Encodes text into binary codes
5. Decodes encoded data and writes to output files

📄 Example Files

• letter.txt – input text with character frequency
• source.txt – raw input text to encode
• encoded.txt – Huffman-encoded binary output
• decoded.txt – decoded text output

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🌳 2. BinarySearchTree

Folder: BinarySearchTree/
Main Concepts: Node-based tree structure, recursion, searching, and traversal
Core Classes: BinarySearchTree, TNode

🧩 Overview

Implementation of a Generic Binary Search Tree (BST) supporting all major operations, including node insertion, traversal, searching, and height calculation.

🔍 Features

• Recursive and iterative node insertion
• In-order, pre-order, and post-order traversals
• Search operations (recursive and iterative)
• Deletion of nodes (with zero, one, or two children)
• Finding in-order successors
• Height and node count calculation
• Basic bubble sort for array data

🧠 Example Flow

1. Insert integer elements
2. Print traversals in order
3. Search for values and display tree height
4. Find in-order successor of a given node
5. Delete elements while maintaining BST properties

💻 Example Code Snippet

BinarySearchTree<Integer> tree = new BinarySearchTree<>();
tree.insert(10);
tree.insert(5);
tree.insert(15);
tree.inOrder();
System.out.println("Height: " + tree.findHeight());

🌳 3. LinkedListStackQueue

Folder: LinkedListStackQueue/
Main Concepts: Dynamic data structures — Linked List, Stack, Circular Queue
Core Classes: LinkedList, Node, CircularQueue, Stack

🧩 Overview

This section focuses on implementing and optimizing data structures for search efficiency, memory tracking, and performance measurement.

🔍 Features

• Insertions (front, end, sorted)
• Memory access tracking for efficiency testing
• Value search and removal while maintaining original order
• Supports enqueue, dequeue, and display operations
• Bubble sorting implementation
• Generic queue implementation with circular indexing

🧠 Example Flow

1. Reads integer lists from text files
2. Inserts unique values into linked lists
3. Applies “move-to-front” optimization for frequent searches 4.Measures execution time and memory access counts 5.Demonstrates stack comparison and circular queue usage

💻 Example Code Snippet

CircularQueue<Integer> queue = new CircularQueue<>(Integer.class, 5);
queue.enQueue(10);
queue.enQueue(20);
queue.deQueue();
queue.display();

End of the README

Feel free to explore each code in detail, modify parameters as needed. If you have questions or suggestions, please open an issue or submit a pull request.

• Email: catsudeebrar@gmail.com