Dynamic Pattern Matching with Wildcards

TL;DR

This paper introduces a dynamic pattern matching algorithm with wildcards, achieving sublinear update and query times under certain conditions, and establishes lower bounds based on the SETH hypothesis.

Contribution

It presents the first truly sublinear algorithms for dynamic pattern matching with wildcards, including special cases with few non-wildcard symbols, and provides conditional lower bounds.

Findings

Achieves O(n log^2 n) preprocessing and sublinear update/query times for wildcard pattern matching.

Provides a conditional lower bound based on SETH for truly sublinear update times when k=Ω(log n).

Develops specialized sublinear algorithms for patterns with few non-wildcard symbols, including two non-wildcards case.

Abstract

We study the fully dynamic pattern matching problem where the pattern may contain up to kwildcard symbols, each matching any symbol of the alphabet. Both the text and the pattern are subject to updates (insert, delete, change). We design an algorithm with O(nlog^2 n) preprocessing and update/query time O(knk/k+1 + k2 log n). The bound is truly sublinear for a constant k, and sublinear when k= o(log n). We further complement our results with a conditional lower bound: assuming subquadratic preprocessing time, achieving truly sublinear update time for the case k = {\Omega}(log n) would contradict the Strong Exponential Time Hypothesis (SETH). Finally, we develop sublinear algorithms for two special cases: - If the pattern contains w non-wildcard symbols, we give an algorithm with preprocessing time O(nw) and update time O(w + log n), which is truly sublinear whenever wis truly sublinear. - Using FFT technique combined with block decomposition, we design a deterministic truly sublinear algorithm with preprocessing time O(n^1.8) and update time O(n^0.8 log n) for the case that there are at most two non-wildcards.