# Regular Expression Search on Compressed Text

## TL;DR

This paper introduces a new algorithm for efficiently searching regular expressions in compressed text, significantly reducing search time compared to existing methods by leveraging specialized data structures.

## Contribution

It presents a novel algorithm and data structures for regular expression search in compressed text, achieving near-optimal complexity and improved performance over prior approaches.

## Key findings

- The algorithm reports match counts in linear time relative to compressed size.
- The implementation --zearch-- is up to 25% faster than current state-of-the-art methods.
- Efficient data structures enable near-optimal complexity bounds.

## Abstract

We present an algorithm for searching regular expression matches in compressed text. The algorithm reports the number of matching lines in the uncompressed text in time linear in the size of its compressed version. We define efficient data structures that yield nearly optimal complexity bounds and provide a sequential implementation --zearch-- that requires up to 25% less time than the state of the art.