Random Access in Persistent Strings and Segment Selection

TL;DR

This paper introduces a space-efficient data structure for random access in collections of similar strings represented by trees, achieving optimal query times and extending to a geometric segment selection problem.

Contribution

It presents a novel $O(n)$ space data structure supporting $O(rac{\log n}{\log \log n})$ query time for random access in persistent strings, improving previous bounds and proving optimality.

Findings

Achieves $O(n)$ space and $O(rac{\log n}{\log \log n})$ query time for string collections.

Reduces string random access to a geometric segment selection problem.

Proves the optimality of the query time for near-linear space solutions.

Abstract

We consider compact representations of collections of similar strings that support random access queries. The collection of strings is given by a rooted tree where edges are labeled by an edit operation (inserting, deleting, or replacing a character) and a node represents the string obtained by applying the sequence of edit operations on the path from the root to the node. The goal is to compactly represent the entire collection while supporting fast random access to any part of a string in the collection. This problem captures natural scenarios such as representing the past history of an edited document or representing highly-repetitive collections. Given a tree with $n$ nodes, we show how to represent the corresponding collection in $O(n)$ space and $O(\log n/ \log \log n)$ query time. This improves the previous time-space trade-offs for the problem. Additionally, we show a lower bound proving that the query time is optimal for any solution using near-linear space. To achieve our bounds for random access in persistent strings we show how to reduce the problem to the following natural geometric selection problem on line segments. Consider a set of horizontal line segments in the plane. Given parameters $i$ and $j$, a segment selection query returns the $j$th smallest segment (the segment with the $j$th smallest $y$-coordinate) among the segments crossing the vertical line through $x$-coordinate $i$. The segment selection problem is to preprocess a set of horizontal line segments into a compact data structure that supports fast segment selection queries. We present a solution that uses $O(n)$ space and support segment selection queries in $O(\log n/ \log \log n)$ time, where $n$ is the number of segments. Furthermore, we prove that that this query time is also optimal for any solution using near-linear space.