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The longest common subsequence (LCS) problem is a central problem in stringology that finds the longest common subsequence of given two strings $A$ and $B$. More recently, a set of four constrained LCS problems (called generalized…

Data Structures and Algorithms · Computer Science 2020-01-17 Kohei Yamada , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda

Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable…

Data Structures and Algorithms · Computer Science 2018-11-06 Kensuke Sakai , Tatsuya Ohno , Keisuke Goto , Yoshimasa Takabatake , Tomohiro I , Hiroshi Sakamoto

Despite consistently yielding the best compression on repetitive text collections, the Lempel-Ziv parsing has resisted all attempts at offering relevant guarantees on the cost to access an arbitrary symbol. This makes it less attractive for…

Data Structures and Algorithms · Computer Science 2024-04-24 Zsuzsanna Lipták , Francesco Masillo , Gonzalo Navarro

Motivated by the imminent growth of massive, highly redundant genomic databases, we study the problem of compressing a string database while simultaneously supporting fast random access, substring extraction and pattern matching to the…

Data Structures and Algorithms · Computer Science 2012-11-01 Travis Gagie , Paweł Gawrychowski , Christopher Hoobin , Simon J. Puglisi

An LZ-like factorization of a string divides it into factors, each being either a single character or a copy of a preceding substring. While grammar-based compression schemes support efficient random access with space linear in the…

Data Structures and Algorithms · Computer Science 2026-01-22 Hiroki Shibata , Yuto Nakashima , Yutaro Yamaguchi , Shunsuke Inenaga

Compressed indexing enables powerful queries over massive and repetitive textual datasets using space proportional to the compressed input. While theoretical advances have led to highly efficient index structures, their practical…

Data Structures and Algorithms · Computer Science 2025-10-24 Ankith Reddy Adudodla , Dominik Kempa

Real-world data often comes in compressed form. Analyzing compressed data directly (without decompressing it) can save space and time by orders of magnitude. In this work, we focus on fundamental sequence comparison problems and try to…

Data Structures and Algorithms · Computer Science 2021-12-14 Arun Ganesh , Tomasz Kociumaka , Andrea Lincoln , Barna Saha

Prefix caching is a key latency optimization for autoregressive LLM serving, yet existing systems assume dense per-token key/value reuse. State-space models change the structure of the problem: a recurrent layer can resume from a single…

Machine Learning · Computer Science 2026-05-08 Mikhail Shirokikh , Sergey Nikolenko

In this paper we investigate the problem of building a static data structure that represents a string s using space close to its compressed size, and allows fast access to individual characters of s. This type of structures was investigated…

Computational Complexity · Computer Science 2012-05-04 Shiteng Chen , Elad Verbin , Wei Yu

This paper shows that a simple algorithm produces the {\em all-prefixes-LCSs-graph} in $O(mn)$ time for two input sequences of size $m$ and $n$. Given any prefix $p$ of the first input sequence and any prefix $q$ of the second input…

Data Structures and Algorithms · Computer Science 2011-03-09 Ronald I. Greenberg

A compressed self-index stores a string in compressed form while supporting locate queries without decompression. For highly repetitive strings (arising in web crawls, versioned documents, and genomic collections), static self-indexes can…

Data Structures and Algorithms · Computer Science 2026-04-29 Takaaki Nishimoto , Yasuo Tabei

LZ77-based compression schemes compress the input text by replacing factors in the text with an encoded reference to a previous occurrence formed by the couple (length, offset). For a given factor, the smallest is the offset, the smallest…

Data Structures and Algorithms · Computer Science 2012-11-22 Maxime Crochemore , Alessio Langiu , Filippo Mignosi

Suffix trees are a fundamental data structure in stringology, but their space usage, though linear, is an important problem for its applications. We design and implement a new compressed suffix tree targeted to highly repetitive texts, such…

Data Structures and Algorithms · Computer Science 2019-02-12 Manuel Cáceres , Gonzalo Navarro

One of the most fundamental method for comparing two given strings $A$ and $B$ is the longest common subsequence (LCS), where the task is to find (the length) of an LCS of $A$ and $B$. In this paper, we deal with the STR-IC-LCS problem…

Data Structures and Algorithms · Computer Science 2024-05-21 Yuki Yonemoto , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai

We consider the problem of {\em restructuring} compressed texts without explicit decompression. We present algorithms which allow conversions from compressed representations of a string $T$ produced by any grammar-based compression…

Data Structures and Algorithms · Computer Science 2011-07-15 Keisuke Goto , Shirou Maruyama , Shunsuke Inenaga , Hideo Bannai , Hiroshi Sakamoto , Masayuki Takeda

We raise the question of approximating the compressibility of a string with respect to a fixed compression scheme, in sublinear time. We study this question in detail for two popular lossless compression schemes: run-length encoding (RLE)…

Data Structures and Algorithms · Computer Science 2007-06-11 Sofya Raskhodnikova , Dana Ron , Ronitt Rubinfeld , Adam Smith

Lempel-Ziv-Double (LZD) is a variation of the LZ78 compression scheme that achieves better compression on repetitive datasets. Nevertheless, prior research has identified computational inefficiencies and a weakness in its compressibility…

Data Structures and Algorithms · Computer Science 2025-05-05 Linus Götz , Dominik Köppl

We show that if DTIME[2^{O(n)}] is not included in DSPACE[2^{o(n)}], then, for every set B in PSPACE, all strings x in B of length n can be represented by a string compressed(x) of length at most log (|B^{=n}|) + O(log n), such that a…

Computational Complexity · Computer Science 2011-04-15 Marius Zimand

Given a string $S$ of length $N$ on a fixed alphabet of $\sigma$ symbols, a grammar compressor produces a context-free grammar $G$ of size $n$ that generates $S$ and only $S$. In this paper we describe data structures to support the…

Data Structures and Algorithms · Computer Science 2014-08-15 Djamal Belazzougui , Simon J. Puglisi , Yasuo Tabei

We introduce the first grammar-compressed representation of a sequence that supports searches in time that depends only logarithmically on the size of the grammar. Given a text $T[1..u]$ that is represented by a (context-free) grammar of…

Data Structures and Algorithms · Computer Science 2011-10-21 Francisco Claude , Gonzalo Navarro