LZ4.AI.Sharp 1.0.2

LZ4.AI.Sharp

⚠️ AI-Generated Code — This entire library was migrated from C to C# and performance-tuned using GitHub Copilot.

A high-performance C#/.NET implementation of the LZ4 compression algorithm, featuring both fast and high-compression modes. This library was created as an AI-assisted port of the LZ4 reference implementation to demonstrate modern AI-powered code migration and optimization.

Features

• Fast Compression (LZ4Codec) — Optimized for speed with competitive compression ratios
• High Compression (LZ4HC) — Better compression ratios at slower speeds
• Frame Format (LZ4Frame) — Stream-oriented API with checksums and metadata
• XXHash — Fast non-cryptographic hash function
• Pure Managed C# — No external native library dependencies, runs on any .NET platform (uses unsafe code for performance)
• Zero Allocations — Work directly with byte arrays and spans

Installation

dotnet add package LZ4.AI.Sharp

Quick Start

Fast Compression

using LZ4Sharp;

byte[] input = GetYourData();
byte[] compressed = new byte[LZ4Codec.CompressBound(input.Length)];
// accel: 1 (higher compression) to 65537 (faster), default is 1
int compressedSize = LZ4Codec.CompressFast(input, compressed, input.Length, compressed.Length, acceleration: 1);

byte[] decompressed = new byte[input.Length];
LZ4Codec.DecompressSafe(compressed, decompressed, compressedSize, decompressed.Length);

High Compression

using LZ4Sharp;

byte[] compressed = new byte[LZ4HC.CompressBound(input.Length)];
int compressedSize = LZ4HC.CompressHC(input, compressed, input.Length, compressed.Length);

Performance

See BENCHMARKS.md for detailed performance results on JSON and Silesia corpus datasets.

Highlights (Intel N100, .NET 10):

• JSON dataset: ratios 0.29–0.77 vs K4os (1.3x–3.4x faster)
• Silesia corpus (accel=1): ratios 0.09–1.00 vs K4os (up to 11.1x faster)
• Silesia: faster in 11/12 files at accel=1
• Compression ratios: Match the reference implementation

Testing

The test suite includes:

• Unit Tests — Comprehensive algorithm correctness tests
• Compatibility Tests — Cross-validation with K4os.Compression.LZ4 to ensure interoperability
• Round-trip Tests — Compression/decompression verification

All tests verify that LZ4Sharp produces output compatible with other LZ4 implementations.

Development

# Build
dotnet build src/LZ4Sharp.sln -c Release

# Test
dotnet test src/LZ4Sharp.sln -c Release

# Run benchmarks
dotnet run --project src/LZ4Sharp.Benchmarks -c Release

# Package
dotnet pack src/LZ4Sharp/LZ4Sharp.csproj -c Release

AI Provenance

This library is 100% AI-generated code:

1. Migration — Ported from C reference implementation using GitHub Copilot
2. Optimization — Performance-tuned through iterative AI-assisted refinement
3. Testing — Test cases and benchmarks created with AI assistance

The project demonstrates AI capabilities in code translation, optimization, and maintaining algorithmic correctness while adapting to different language paradigms.

Attribution

• Based on the LZ4 reference implementation by Yann Collet
• Not affiliated with the upstream LZ4 project
• See THIRD-PARTY-NOTICES.md for license details

License

MIT License — See LICENSE for details.