Rank, select and access in grammar-compressed strings

TL;DR

This paper develops data structures for efficient rank, select, and access operations on grammar-compressed strings, achieving near-optimal space and time bounds and establishing complexity lower bounds.

Contribution

It introduces novel data structures for rank, select, and access in grammar-compressed strings, with tight bounds and hardness results for improvements.

Findings

Support rank and select in $O( olinebreak ext{log} N)$ time with $O(n ext{log} N)$ bits.

Support rank and select in $O( ext{log} N / ext{log} ext{log} N)$ time with $O(n ext{log} (N/n) ( ext{log} N)^{1+ ext{epsilon}})$ bits.

Achieve access query time close to the lower bound with space proportional to the grammar size.

Abstract

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 following operations on a grammar-compressed string: $\mbox{rank}_c(S,i)$ (return the number of occurrences of symbol $c$ before position $i$ in $S$); $\mbox{select}_c(S,i)$ (return the position of the $i$th occurrence of $c$ in $S$); and $\mbox{access}(S,i,j)$ (return substring $S[i,j]$). For rank and select we describe data structures of size $O(n\sigma\log N)$ bits that support the two operations in $O(\log N)$ time. We propose another structure that uses $O(n\sigma\log (N/n)(\log N)^{1+\epsilon})$ bits and that supports the two queries in $O(\log N/\log\log N)$, where $\epsilon>0$ is an arbitrary constant. To our knowledge, we are the first to study the asymptotic complexity of rank and select in the grammar-compressed setting, and we provide a hardness result showing that significantly improving the bounds we achieve would imply a major breakthrough on a hard graph-theoretical problem. Our main result for access is a method that requires $O(n\log N)$ bits of space and $O(\log N+m/\log_\sigma N)$ time to extract $m=j-i+1$ consecutive symbols from $S$. Alternatively, we can achieve $O(\log N/\log\log N+m/\log_\sigma N)$ query time using $O(n\log (N/n)(\log N)^{1+\epsilon})$ bits of space. This matches a lower bound stated by Verbin and Yu for strings where $N$ is polynomially related to $n$.