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Circular Dictionary Matching Using Extended BWT

Authors Wing-Kai Hon , Rahul Shah , Sharma V. Thankachan

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ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • String algorithms
  • Burrows-Wheeler transformation
  • suffix trees
  • succinct data structures

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Abstract

The dictionary matching problem involves preprocessing a set of strings (patterns) into a data structure that efficiently identifies all occurrences of these patterns within a query string (text). In this work, we investigate a variation of this problem, termed circular dictionary matching, where the patterns are circular, meaning their cyclic shifts are also considered valid patterns. Such patterns naturally occur in areas such as bioinformatics and computational geometry. Based on the extended Burrows-Wheeler Transformation (eBWT), we design a space-efficient solution for this problem. Specifically, we show that a dictionary of d circular patterns of total length n can be indexed in nlog σ + O(n+dlog n+σ log n) bits of space and support circular dictionary matching on a query text T in O((|T|+occ)log n) time, where σ represents the size of the underlying alphabet and occ represents the output size.

Cite As Get BibTex

Wing-Kai Hon, Rahul Shah, and Sharma V. Thankachan. Circular Dictionary Matching Using Extended BWT. In The Expanding World of Compressed Data: A Festschrift for Giovanni Manzini's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 131, pp. 11:1-11:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.Manzini.11

Author Details

Wing-Kai Hon
  • National Tsing Hua University, Hsinchu, Taiwan
Rahul Shah
  • Louisiana State University, Baton Rouge, LA, USA
Sharma V. Thankachan
  • North Carolina State University, Raleigh, NC, USA

Funding

Supported by the US National Science Foundation (NSF) under Grant Numbers 2137057, 2434261 (R Shah) and 2315822 (S Thankachan).

Acknowledgements

We thank all the anonymous reviewers (and Mano Prakash Parthasarathi) for their valuable feedback, which helped improve this paper. We also thank Travis Gagie for pointing out the independent work by Cotumaccio [Nicola Cotumaccio, 2025].

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