The most widely used general purpose compressors (gzip, zstd) are based on LZ77. It encodes data by referencing earlier occurrences of the same data within a sliding window.

• Universal Compression: Theoretically, LZ77 achieves the entropy rate of any stationary process, making it a versatile tool for diverse data types.
• Efficient Match Finding: Utilizes a hash-based indexing approach for quick identification of repeated sequences.
• Adaptability: Effective for text, binary files, and images.

• Building the Project:

  make lz77

• Compression:

  ./lz77 -encode [input file] [output file]

• Decompression:

  ./lz77 -decode [input file] [output file]

• LZ77Context: Manages the state, including buffers, hash table, and counters.

• UpdateHash: Updates index references in the hash table.
• FindMatch: Identifies the longest match in the input data.
• WriteLiteral: Handles literal (uncompressed) data blocks.
• WriteCompressedBlock: Manages the encoding of compressed data.
• LZ77Encode: Core compression function.
• LZ77Decode: Core decompression function.

1. Memory Efficiency: The entire output buffer is held in memory during decompression, which could be optimized for large files.
2. Compression Optimality: The current greedy parsing strategy may not always yield the best compression ratio. Future updates could explore more sophisticated strategies.
3. Special Case Handling: Enhancements are needed for better handling of long repeating sequences.

Below is a comparison of LZ77 compression against gzip across various file types:

Data for some files were sourced from the Squash Compression Corpus.

All sizes are in bytes.

For further reading and understanding of the underlying principles of data compression, refer to Stanford EE274: Data Compression Course Notes.