A compressed dynamic self-index for highly repetitive text collections

TL;DR

This paper introduces TST-index, a new compressed dynamic self-index for highly repetitive texts that significantly improves pattern search speed while supporting dynamic updates.

Contribution

The paper presents the first compressed dynamic self-index that combines fast pattern search with dynamic update capabilities for highly repetitive texts.

Findings

Pattern search speed is significantly improved with TST-index.

TST-index supports dynamic updates in highly repetitive texts.

Experimental results demonstrate superior performance on benchmark datasets.

Abstract

We present a novel compressed dynamic self-index for highly repetitive text collections. Signature encoding is a compressed dynamic self-index for highly repetitive texts and has a large disadvantage that the pattern search for short patterns is slow. We improve this disadvantage for faster pattern search by leveraging an idea behind truncated suffix tree and present the first compressed dynamic self-index named TST-index that supports not only fast pattern search but also dynamic update operation of index for highly repetitive texts. Experiments using a benchmark dataset of highly repetitive texts show that the pattern search of TST-index is significantly improved.