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Compressed Literature

Overview

This data structures project implements the Huffman coding algorithm to compress text files, using the example of Leo Tolstoy’s "War and Peace". The implementation includes building and traversing a Huffman tree, encoding and decoding messages, and handling binary file operations.

Learning Outcomes

  • Utilized a priority queue data structure for Huffman coding.
  • Developed a Huffman tree for encoding and decoding text.
  • Implemented efficient methods for writing to and reading from binary files.

Features

  • Character Frequency Counting: Counts the frequency of characters in a text file.
  • Huffman Tree Construction: Builds a Huffman tree based on character frequency.
  • Encoding and Decoding: Encodes text into compressed format and optionally decodes it.
  • Efficient Binary File Operations: Writes the compressed data to a binary file, ensuring efficient storage.

Technologies Used

  • Java
  • Custom Implemented Data Structures: Array List, Linked List, Ordered ListPriority Queues, Trees
  • Algorithms: Huffman Coding
  • File I/O for reading from and writing to files

Challenges and Solutions

  • Efficiency in Large Files: Faced challenges in efficiently handling large text files. Optimized file reading and writing processes to minimize processing time.
  • Binary Data Handling: Implementing binary file operations was initially challenging. Developed a deeper understanding of low-level I/O operations through this project.
  • Complex Data Structures: Utilizing and manipulating complex data structures like trees and priority queues was crucial. This enhanced my skills in understanding and applying advanced data structures.

Sample Output

Note: Program runtimes will vary based on machine hardware

Reading input file "./WarAndPeace.txt"... 3291642 characters in 66 milliseconds.
Finding words and adding them to a linked list... in 333 milliseconds.
The linked list has a length of 570240.
Counting frequencies of characters... 86 unique characters found in 229
milliseconds.
Building a Huffman tree and reading codes... in 2 milliseconds.
Encoding message... in 280 milliseconds.
Writing compressed file... 1875165 bytes written in 2 milliseconds.