Practical Linear-Time Computation of Smallest Suffixient Sets

2026-06-29

AI Summary

Existing algorithms for constructing minimal suffix covers struggle to achieve both time and space efficiency on large-scale repetitive texts. This work proposes the first practical, linear-time, single-pass algorithm for building minimal suffix covers, leveraging a suffix array–based traversal strategy combined with compact data representations and streaming techniques. By processing the input in one sequential scan, the method avoids redundant computations and excessive memory usage inherent in prior approaches. Experimental results demonstrate that the proposed algorithm significantly outperforms existing implemented methods in both construction speed and memory footprint, effectively achieving a superior trade-off between time and space complexity for suffix cover construction on repetitive datasets.

Abstract

Suffixient arrays are recent structures that have attracted attention because they offer relevant pattern matching functionality in less asymptotic space than the Run-Length BWT, the de-facto standard to index highly repetitive string collections. Various algorithms exist for building them from the suffix array data structures. We present the first construction algorithm that is (i) linear-time, (ii) one-pass over the structures, and (iii) implemented and practical. This makes the construction particularly useful on large text collections, which we demonstrate empirically by showing that it dominates the space/time tradeoff map of the implemented constructions.

Problem

• Suffixient arrays
• Smallest Suffixient Sets
• linear-time construction
• highly repetitive strings
• pattern matching

Innovation

• linear-time
• one-pass
• suffixient arrays
• practical algorithm
• space-efficient indexing