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Huffman Encoding Study

Welcome to the Huffman Encoding Study repository! This project benchmarks various data compression algorithms to evaluate their performance and efficiency. The key algorithms analyzed include:

  • Huffman Encoding
  • Burrows-Wheeler Transform (BWT)
  • Run-Length Encoding (RLE)
  • Combined Approaches: BWT + RLE + Huffman Encoding

Features

  • Compression Ratio Calculation: Measures how well each algorithm compresses data.
  • Performance Metrics: Tracks compression and decompression times.
  • Space Efficiency: Analyzes memory usage during compression and decompression.
  • Diverse Testing: Evaluates algorithms with different input sizes and types.

Getting Started

  1. Clone the Repository:
git clone https://github.com/ml3m/huffman_encoding_study.git

Navigate to the Project Directory:

cd huffman_encoding_study

Build the Project:

go build -o compression_benchmark

Run the Benchmark:

./compression_benchmark [input_file]

Results The benchmarking script compares:

Simple Encoding Huffman Encoding BWT + Huffman Encoding RLE + Huffman Encoding BWT + RLE + Huffman Encoding Results include compression sizes, performance times, and compression ratios.

Contributing Contributions are welcome! To contribute, please fork the repository and submit a pull request. For issues or feature requests, open an issue on GitHub.

Key Sections:

  1. Overview: Briefly describes what the project does.
  2. Features: Lists the main features and metrics of the benchmarks.
  3. Getting Started: Provides instructions on how to clone, build, and run the project.
  4. Results: Describes what the benchmarking script evaluates.
  5. Contributing: Information on how others can contribute to the project.

Feel free to modify any sections or add more information to fit your needs!