Performance Optimization

libmagic-rs is designed for high performance while maintaining safety and correctness.

Performance Targets

• Speed: Within 10% of C libmagic performance
• Memory: Comparable memory usage to C implementation
• Startup: Faster initialization with rule caching
• Scalability: Efficient handling of large files and rule sets

Optimization Strategies

Memory-Mapped I/O

• Avoid loading entire files into memory
• Leverage OS page cache for frequently accessed files
• Zero-copy buffer operations where possible

Rule Evaluation

• Lazy evaluation: only process rules when necessary
• Early termination on definitive matches
• Optimized rule ordering based on match probability

String Matching

• Aho-Corasick algorithm for multi-pattern searches
• Boyer-Moore for single pattern searches
• Binary-safe string operations

Caching

• Compiled rule caching to avoid re-parsing
• Result caching for frequently analyzed files
• Intelligent cache invalidation

Benchmarking

Performance benchmarks will be available using the criterion crate:

cargo bench

Profiling

Tools for performance analysis:

• cargo flamegraph for CPU profiling
• valgrind for memory analysis
• perf for detailed system-level profiling

Implementation Status

• Basic performance benchmarks
• Memory-mapped I/O optimization
• Rule evaluation optimization
• String matching optimization
• Caching implementation
• Performance regression testing