# A Framework of Dynamic Data Structures for String Processing

## TL;DR

This paper introduces DYNAMIC, a C++ library of dynamic compressed data structures for string processing, demonstrating their theoretical efficiency and practical advantages in space savings over traditional methods.

## Contribution

It presents a comprehensive framework of dynamic compressed data structures, with theoretical bounds and empirical validation, and applies them to improve string compression algorithms.

## Key findings

- Dynamic structures are up to 1000 times more space-efficient.
- Theoretical bounds closely match empirical results.
- Applications show significant space savings in compression algorithms.

## Abstract

In this paper we present DYNAMIC, an open-source C++ library implementing dynamic compressed data structures for string manipulation. Our framework includes useful tools such as searchable partial sums, succinct/gap-encoded bitvectors, and entropy/run-length compressed strings and FM-indexes. We prove close-to-optimal theoretical bounds for the resources used by our structures, and show that our theoretical predictions are empirically tightly verified in practice. To conclude, we turn our attention to applications. We compare the performance of four recently-published compression algorithms implemented using DYNAMIC with those of state-of-the-art tools performing the same task. Our experiments show that algorithms making use of dynamic compressed data structures can be up to three orders of magnitude more space-efficient (albeit slower) than classical ones performing the same tasks.