We prove that for every integer n > 0 and for every alphabet Σ_k of size k ≥ 3, there exist words of length n whose Burrows-Wheeler Transform (BWT) is totally unclustered, i.e., it consists of exactly n runs with no two consecutive equal symbols. These words represent the worst-case behavior of the clustering effect of the BWT. We also establish a lower bound on their number. This contrasts with the binary case, where the existence of infinitely many totally unclustered BWT images is still an open problem, related to Artin’s conjecture on primitive roots.

We say a finite word x is a palindromic periodicity if there exist two palindromes p and s such that |x| ≥ |ps| and x is a prefix of the infinite periodic word (ps)^ω = pspsps⋯. In this paper we examine the palindromic periodicities occurring in some classical infinite words, such as Sturmian words, episturmian words, the Thue-Morse word, the period-doubling word, the Rudin-Shapiro word, the paperfolding word, and the Tribonacci word, and prove a number of results about them. We also prove results about words with the smallest number of distinct palindromic periodicities.

We define generalized de Bruijn words as those words having a Burrows-Wheeler transform that is a concatenation of permutations of the alphabet. We show that generalized de Bruijn words are in 1-to-1 correspondence with Hamiltonian cycles in the generalized de Bruijn graphs, introduced in the early’80s in the context of network design. When the size of the alphabet is a prime p, we define invertible necklaces as those whose BWT-matrix is non-singular. We show that invertible necklaces of length n correspond to normal bases of the finite field Fpn, and that they form an Abelian group isomorphic to the Reutenauer group RGnp. Using known results in abstract algebra, we can make a bridge between generalized de Bruijn words and invertible necklaces. In particular, we highlight a correspondence between binary de Bruijn words of order d + 1, binary necklaces of length 2d having an odd number of 1’s, invertible BWT matrices of size 2d × 2d, and normal bases of the finite field F22d.

We study how the application of morphisms affects the number r of equal-letter runs in the Burrows–Wheeler Transform (BWT). This parameter has emerged as a key repetitiveness measure in compressed indexing. We focus on the notion of BWT-run sensitivity after application of morphisms. For binary alphabets, we characterize the class of injective morphisms that preserve the number of BWT-runs up to a bounded additive increase by showing that it coincides with the known class of primitivity-preserving morphisms, which are those that map primitive words to primitive words. We further prove that deciding whether a given binary morphism has bounded BWT-run sensitivity is possible in polynomial time with respect to the total length of the images of the two letters. Additionally, we explore new structural and combinatorial properties of synchronizing and recognizable morphisms. These results establish new connections between BWT-based compressibility, code theory, and symbolic dynamics.

Motivation. Text indexing is a fundamental and well-studied problem. Classic solutions to this problem either replace the original text with a compressed representation, e.g., the FM-index and its variants, or keep it uncompressed but attach some redundancy - an index - to accelerate matching, e.g., the suffix array. The former solutions thus retain excellent compressed space, but are practically slow to construct and query. The latter approaches, instead, sacrifice space efficiency but are typically faster; for example, the suffix array takes much more space than the text itself for commonly used alphabets, like ASCII or DNA, but it is very fast to construct and query. Methods. In this paper, we show that efficient text indexing can be achieved using just a small extra space on top of the original text, provided that the query patterns are sufficiently long. More specifically, we develop a new indexing paradigm in which a sketch of a query pattern is first matched against a sketch of the text. Once candidate matches are retrieved, they are verified using the original text. This paradigm is thus universal in the sense that it allows us to use any solution to index the sketched text, like a suffix array, FM-index, or r-index. Results. We explore both the theory and the practice of this universal framework. With an extensive experimental analysis, we show that, surprisingly, universal indexes can be constructed much faster than their unsketched counterparts and take a fraction of the space, as a direct consequence of (i) having a lower bound on the length of patterns and (ii) working in sketch space. Furthermore, these data structures have the potential of retaining or even improving query time, because matching against the sketched text is faster and verifying candidates can be theoretically done in constant time per occurrence (or, in practice, by short and cache-friendly scans of the text). Finally, we discuss some important applications of this novel indexing paradigm to computational biology. We hypothesize that such indexes will be particularly effective when the queries are sufficiently long, and so we demonstrate applications in long-read mapping.

We exhibit combinatorial results on Christoffel words and binary balanced words that are motivated by their geometric interpretation as approximations of digital segments. We give a closed formula for counting the exact number of balanced words with a zeroes and b ones. We also study minimal non-balanced words.

Shannon's entropy is a definitive lower bound for statistical compression. Unfortunately, no such clear measure exists for the compressibility of repetitive strings. Thus, ad hoc measures are employed to estimate the repetitiveness of strings, e.g., the size $z$ of the Lempel-Ziv parse or the number $r$ of equal-letter runs of the Burrows-Wheeler transform. A more recent one is the size $γ$ of a smallest string attractor. Let $T$ be a string of length $n$. A string attractor of $T$ is a set of positions of $T$ capturing the occurrences of all the substrings of $T$. Unfortunately, Kempa and Prezza [STOC 2018] showed that computing $γ$ is NP-hard. Kociumaka et al. [LATIN 2020] considered a new measure of compressibility that is based on the function $S_T(k)$ counting the number of distinct substrings of length $k$ of $T$, also known as the substring complexity of $T$. This new measure is defined as $δ= \sup\{S_T(k)/k, k\geq 1\}$ and lower bounds all the relevant ad hoc measures previously considered. In particular, $δ\leq γ$ always holds and $δ$ can be computed in $\mathcal{O}(n)$ time using $Θ(n)$ working space. Kociumaka et al. showed that one can construct an $\mathcal{O}(δ\log \frac{n}δ)$-sized representation of $T$ supporting efficient direct access and efficient pattern matching queries on $T$. Given that for highly compressible strings, $δ$ is significantly smaller than $n$, it is natural to pose the following question: Can we compute $δ$ efficiently using sublinear working space? We address this algorithmic challenge by showing the following bounds to compute $δ$: $\mathcal{O}(\frac{n^3\log b}{b^2})$ time using $\mathcal{O}(b)$ space, for any $b\in[1,n]$, in the comparison model; or $\tilde{\mathcal{O}}(n^2/b)$ time using $\tilde{\mathcal{O}}(b)$ space, for any $b\in[\sqrt{n},n]$, in the word RAM model.

Abstract A wordxthat is absent from a wordyis calledminimalif all its proper factors occur iny. Given a collection ofkwordsy1, … ,ykover an alphabetΣ, we are asked to compute the set $\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$ M{y1,…,yk}ℓ of minimal absent words of length at mostℓof the collection {y1, … ,yk}. The set $\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$ M{y1,…,yk}ℓ contains all the wordsxsuch thatxis absent from all the words of the collection while there existi,j, such that the maximal proper suffix ofxis a factor ofyiand the maximal proper prefix ofxis a factor ofyj. In data compression, this corresponds to computing the antidictionary ofkdocuments. In bioinformatics, it corresponds to computing words that are absent from a genome ofkchromosomes. Indeed, the set $\mathrm {M}^{\ell }_{y}$ Myℓ of minimal absent words of a wordyis equal to $\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$ M{y1,…,yk}ℓ for any decomposition ofyinto a collection of wordsy1, … ,yksuch that there is an overlap of length at leastℓ− 1 between any two consecutive words in the collection. This computation generally requiresΩ(n) space forn= |y| using any of the plenty available $\mathcal {O}(n)$ O(n) -time algorithms. This is because anΩ(n)-sized text index is constructed overywhich can be impractical for largen. We do the identical computation incrementally using output-sensitive space. This goal is reasonable when $\| \mathrm {M}^{\ell }_{\{y_1,\ldots ,y_N\}}\| =o(n)$ ∥M{y1,…,yN}ℓ∥=o(n) , for allN∈ [1,k], where ∥S∥ denotes the sum of the lengths of words in setS. For instance, in the human genome,n≈ 3 × 109but $\| \mathrm {M}^{12}_{\{y_1,\ldots ,y_k\}}\| \approx 10^{6}$ ∥M{y1,…,yk}12∥≈106 . We consider a constant-sized alphabet for stating our results. We show thatall $\mathrm {M}^{\ell }_{y_{1}},\ldots ,\mathrm {M}^{\ell }_{\{y_1,\ldots ,y_k\}}$ My1ℓ,…,M{y1,…,yk}ℓ can be computed in $\mathcal {O}(kn+{\sum }^{k}_{N=1}\| \mathrm {M}^{\ell }_{\{y_1,\ldots ,y_N\}}\| )$ O(kn+∑N=1k∥M{y1,…,yN}ℓ∥) total time using $\mathcal {O}(\textsc {MaxIn}+\textsc {MaxOut})$ O(MaxIn+MaxOut) space, where MaxIn is the length of the longest word in {y1, … ,yk} and $\textsc {MaxOut}=\max \limits \{\| \mathrm {M}^{\ell }_{\{y_1,\ldots ,y_N\}}\| :N\in [1,k]\}$ MaxOut=max{∥M{y1

Suppose an oracle knows a string S that is unknown to us and that we want to determine. The oracle can answer queries of the form “Is s a substring of S?”. In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle σn/4−O(n) queries in order to be able to reconstruct the hidden string, where σ is the size of the alphabet of S and n its length, and gave an algorithm that spends (σ−1)n+O(σn) queries to reconstruct S. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compressor that compresses the string to τ bits, performs q=O(τ) substring queries; this algorithm, however, runs in exponential time. For this reason, the second part of the paper focuses on more time-efficient algorithms whose number of queries is bounded by specific compressibility measures. We first show that any string of length n over an integer alphabet of size σ with rle runs can be reconstructed with [Formula presented]> substring queries in linear time and space. We then present an algorithm that spends q∈O(σglog⁡n) substring queries and runs in O(n(log⁡n+log⁡σ)+q) time using linear space, where g is the size of a smallest straight-line program generating the string.

We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optimally, where d is maximal for any such z-reverse-safe data structure. The construction algorithm takes O(nω log d) time, where ω is the matrix multiplication exponent. We show that, despite the nω factor, our engineered implementation takes only a few minutes to finish for million-letter texts. We further show that plugging our method in data analysis applications gives insignificant or no data utility loss. Finally, we show how our technique can be extended to support applications under a realistic adversary model.

A word x that is absent from a word y is called minimal if all its proper factors occur in y. Given a collection of k words y1, y2,...,ykover an alphabet Σ, we are asked to compute the set M(y1#...#yk)ℓof minimal absent words of length at most ℓ of word y=y1#y2#...#yk, #∉Σ. In data compression, this corresponds to computing the antidictionary of k documents. In bioinformatics, it corresponds to computing words that are absent from a genome of k chromosomes. This computation generally requires Ω(n) space for n=|y| using any of the plenty available O(n)-time algorithms. This is because an Ω(n)-sized text index is constructed over y which can be impractical for large n. We do the identical computation incrementally using output-sensitive space. This goal is reasonable when ||M(y1#...#yN)ℓ|| =o(n), for all N ϵ[1, k]. For instance, in the human genome, n ≈ 3 × 109but ||M (y1#...#yk)12|| ≈ 106. We consider a constant-sized alphabet for stating our results. We show that all M(y1)ℓ,...,M(y1#...#yk)ℓcan be computed in O(kn+ΣN=1k||M(y1#...#(yN)ℓ||) total time using O(MaxIn+MaxOut) space, where MaxIn is the length of the longest word in y1,...,ykand MaxOut=max{||M (y1)#...#(yN)ℓ||:N ϵ[1, k]. Proof-of-concept experimental results are also provided confirming our theoretical findings and justifying our contribution.

A string S[1,n] is a power (or tandem repeat) of order k and period n/k if it can be decomposed into k consecutive equal-length blocks of letters. Powers and periods are fundamental to string processing, and algorithms for their efficient computation have wide application and are heavily studied. Recently, Fici et al. (Proc. ICALP 2016) defined an anti-power of order k to be a string composed of k pairwise-distinct blocks of the same length (n/k, called anti-period). Anti-powers are a natural converse to powers, and are objects of combinatorial interest in their own right. In this paper we initiate the algorithmic study of anti-powers. Given a string S, we describe an optimal algorithm for locating all substrings of S that are anti-powers of a specified order. The optimality of the algorithm follows form a combinatorial lemma that provides a lower bound on the number of distinct anti-powers of a given order: we prove that a string of length n can contain Θ(n2/k) distinct anti-powers of order k.

We give a polynomial-time construction of the set of sequences that satisfy a finite-memory constraint defined by a finite list of forbidden blocks, with a specified set of bit positions unconstrained. Such a construction can be used to build modulation/error-correction codes (ECC codes) like the ones defined by the Immink-Wijngaarden scheme in which certain bit positions are reserved for ECC parity. We give a linear-time construction of a finite-state presentation of a constrained system defined by a periodic list of forbidden blocks. These systems, called periodic-finite-type (PFT) systems, were introduced by Moision and Siegel. Finally, we present a linear-time algorithm for constructing the minimal periodic forbidden blocks of a finite sequence for a given period.