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Anouk Duyster

Publications and source records attributed to Anouk Duyster.

2 recordsLinked to original sources

Random Access in Grammar-Compressed Strings: Optimal Trade-Offs in Almost All Parameter Regimes

A Random Access query to a string $T\in [0..\sigma)^n$ asks for the character $T[i]$ at a given position $i\in [0..n)$. In $O(n\log\sigma)$ bits of space, this fundamental task admits constant-time queries. While this is optimal in the worst case, much research has focused on compressible strings, hoping for smaller data structures that still admit efficient queries. We investigate the grammar-compressed setting, where $T$ is represented by a straight-line grammar. Our main result is a general trade-off that optimizes Random Access time as a function of string length $n$, grammar size (the total length of productions) $g$, alphabet size $\sigma$, data structure size $M$, and word size $w=\Omega(\log n)$ of the word RAM model. For any $M$ with $g\log n 0$ [Belazzougui et al.; ESA'15], [Ganardi, Je\.z, Lohrey; J. ACM 2021]. The only tight lower bound [Verbin and Yu; CPM'13] was $\Omega(\frac{\log n}{\log\log n})$ for $w=\Theta(\log n)$, $n^{\Omega(1)}\le g\le n^{1-\Omega(1)}$, and $M=g\log^{\Theta(1)}n$. In contrast, our result yields tight bounds in all relevant parameters and almost all regimes. Our data structure admits efficient deterministic construction. It relies on novel grammar transformations that generalize contracting grammars [Ganardi; ESA'21]. Beyond Random Access, its variants support substring extraction, rank, and select.

cs.DS

Logarithmic-Time Internal Pattern Matching Queries in Compressed and Dynamic Texts

Internal Pattern Matching (IPM) queries on a text $T$, given two fragments $X$ and $Y$ of $T$ such that $|Y|<2|X|$, ask to compute all exact occurrences of $X$ within $Y$. IPM queries have been introduced by Kociumaka, Radoszewski, Rytter, and Wale\'n [SODA'15 & SICOMP'24], who showed that they can be answered in $O(1)$ time using a data structure of size $O(n)$ and used this result to answer various queries about fragments of $T$. In this work, we study IPM queries on compressed and dynamic strings. Our result is an $O(\log n)$-time query algorithm applicable to any balanced recompression-based run-length straight-line program (RLSLP). In particular, one can use it on top of the RLSLP of Kociumaka, Navarro, and Prezza [IEEE TIT'23], whose size $O\big(\delta \log \frac{n\log \sigma}{\delta \log n}\big)$ is optimal (among all text representations) as a function of the text length $n$, the alphabet size $\sigma$, and the substring complexity $\delta$. Our procedure does not rely on any preprocessing of the underlying RLSLP, which makes it readily applicable on top of the dynamic strings data structure of Gawrychowski, Karczmarz, Kociumaka, {\L}\k{a}cki and Sankowski [SODA'18], which supports fully persistent updates in logarithmic time with high probability.

cs.DS