Pattern Matching with Mismatches and Wildcards

In this work, we address the problem of approximate pattern matching with wildcards. Given a pattern P of length m containing D wildcards, a text T of length n, and an integer k, our objective is to identify all fragments of T within Hamming distance k from P. Our primary contribution is an algorithm with runtime O(n+(D+k)(G+k)· n/m) for this problem. Here, G ≤ D represents the number of maximal wildcard fragments in P. We derive this algorithm by elaborating in a non-trivial way on the ideas presented by [Charalampopoulos et al., FOCS'20] for pattern matching with mismatches (without wildcards). Our algorithm improves over the state of the art when D, G, and k are small relative to n. For instance, if m = n/2, k=G=n^2/5, and D=n^3/5, our algorithm operates in O(n) time, surpassing the Ω(n^6/5) time requirement of all previously known algorithms. In the case of exact pattern matching with wildcards (k=0), we present a much simpler algorithm with runtime O(n+DG· n/m) that clearly illustrates our main technical innovation: the utilisation of positions of P that do not belong to any fragment of P with a density of wildcards much larger than D/m as anchors for the sought (approximate) occurrences. Notably, our algorithm outperforms the best-known O(nlog m)-time FFT-based algorithms of [Cole and Hariharan, STOC'02] and [Clifford and Clifford, IPL'04] if DG = o(mlog m). We complement our algorithmic results with a structural characterization of the k-mismatch occurrences of P. We demonstrate that in a text of length O(m), these occurrences can be partitioned into O((D+k)(G+k)) arithmetic progressions. Additionally, we construct an infinite family of examples with Ω((D+k)k) arithmetic progressions of occurrences, leveraging a combinatorial result on progression-free sets [Elkin, SODA'10].