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Focal Interest
AI Summary of Peer-Reviewed Research

This page presents an AI-generated summary of a published research paper. The original authors did not write or review this article. [See full disclosure ↓]

Publishing process signals: MODERATE — reflects the venue and review process. — venue and review process.

Logarithmic-time pattern matching for compressed and dynamic texts

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Research area:Theoretical computer sciencePattern matchingAlgorithms and Data Compression

What the study found

The study presents an O(log n)-time algorithm for internal pattern matching queries on compressed texts. It also says the method applies to any balanced recompression-based run-length straight-line program and can be used with a dynamic strings data structure that supports fully persistent updates in logarithmic time with high probability.

Why the authors say this matters

The authors say the result is applicable to compressed and dynamic strings, which broadens the setting in which internal pattern matching can be handled. They also note that it can be used on top of a compressed-text representation whose size is optimal as a function of text length n, alphabet size σ, and substring complexity δ.

What the researchers tested

The researchers studied internal pattern matching (IPM) queries, where two fragments X and Y of a text T are given and the task is to compute all exact occurrences of X within Y, under the condition |Y| < 2|X|. They developed an O(log n)-time query algorithm for balanced recompression-based run-length straight-line programs (RLSLPs) and discussed its use with an existing compressed representation and a dynamic strings data structure.

What worked and what didn't

The abstract states that the proposed query algorithm works in O(log n) time for any balanced recompression-based RLSLP. It also says the method does not rely on preprocessing of the underlying RLSLP, which makes it readily applicable to the dynamic strings structure mentioned in the abstract. The abstract does not report failures or negative results.

What to keep in mind

The available summary does not describe experimental evaluation or benchmarks. It also does not state limitations beyond the specific query setting of internal pattern matching with |Y| < 2|X|.

Key points

  • The paper gives an O(log n)-time algorithm for internal pattern matching queries.
  • The method applies to balanced recompression-based run-length straight-line programs.
  • The authors say it can be used with a dynamic strings data structure that supports fully persistent updates in logarithmic time with high probability.
  • The abstract says the approach does not require preprocessing of the underlying RLSLP.
  • The query setting is internal pattern matching for fragments X and Y with |Y| < 2|X|.

Disclosure

Research title:
Logarithmic-time pattern matching for compressed and dynamic texts
Authors:
Anouk Duyster, Tomasz Kociumaka
Institutions:
Max Planck Institute for Informatics
Publication date:
2026-02-23
DOI:
10.1007/s00224-026-10266-x
OpenAlex record:
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AI provenance: This post was generated by OpenAI. The original authors did not write or review this post.

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