Implement string matching benchmarking suite

Create a comprehensive benchmarking suite specifically for string matching algorithms:

## Algorithms to benchmark:
- Naive string matching
- Knuth-Morris-Pratt (KMP)
- Boyer-Moore
- Rabin-Karp
- Aho-Corasick
- Z algorithm
- Suffix tree/array based approaches

## Benchmark scenarios:
- Short patterns in long texts
- Long patterns in long texts
- Multiple pattern matching
- Approximate string matching
- DNA/genomic sequence matching
- Natural language texts
- Random string generation

## Metrics to capture:
- Preprocessing time
- Matching time
- Memory usage
- Number of character comparisons
- Number of text accesses

## Features:
- Automatic test case generation
- Performance visualization
- Algorithm behavior analysis
- Best algorithm recommendation based on input

This benchmarking suite will provide an empirical comparison of string matching algorithms across different types of inputs, helping users select the most appropriate algorithm for their specific use case.