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Dynamic Pattern Matching with Wildcards
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AI
DOI：10.4230/LIPIcs.STACS.2026.68.png)
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Abstract
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We study the fully dynamic pattern matching problem where the pattern may contain up to k wildcard 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(n log(2) n) preprocessing and update/query time (O) over tilde (kn(k/k+1) + k(2) 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 w is 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.
Keywords:
pattern matching
wildcards
dynamic algorithms
string algorithms
data structures
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