Minimal Absent Words on Run-Length Encoded Strings

TL;DR

This paper develops methods to compute minimal absent words directly from run-length encoded strings, providing bounds and a compact data structure that efficiently reports all such words.

Contribution

It introduces the first approach for computing MAWs from RLE-compressed strings, including bounds and an optimal reporting data structure.

Findings

Bounds for the number of MAWs in most RLE-based categories

A compact data structure with O(m) space

Efficient reporting of all MAWs in optimal time

Abstract

A string $w$ is called a minimal absent word (MAW) for another string $T$ if $w$ does not occur (as a substring) in $T$ and any proper substring of $w$ occurs in $T$. State-of-the-art data structures for reporting the set $\mathsf{MAW}(T)$ of MAWs from a given string $T$ of length $n$ require $O(n)$ space, can be built in $O(n)$ time, and can report all MAWs in $O(|\mathsf{MAW}(T)|)$ time upon a query. This paper initiates the problem of computing MAWs from a compressed representation of a string. In particular, we focus on the most basic compressed representation of a string, run-length encoding (RLE), which represents each maximal run of the same characters $a$ by $a^p$ where $p$ is the length of the run. Let $m$ be the RLE-size of string $T$. After categorizing the MAWs into five disjoint sets $\mathcal{M}_1$, $\mathcal{M}_2$, $\mathcal{M}_3$, $\mathcal{M}_4$, $\mathcal{M}_5$ using RLE, we present matching upper and lower bounds for the number of MAWs in $\mathcal{M}_i$ for $i = 1,2,4,5$ in terms of RLE-size $m$, except for $\mathcal{M}_3$ whose size is unbounded by $m$. We then present a compact $O(m)$-space data structure that can report all MAWs in optimal $O(|\mathsf{MAW}(T)|)$ time.