There has been a flurry of recent literature studying streaming algorithms for which the input
stream is chosen adaptively by a black-box adversary who observes the output of the …

In the approximate pattern matching problem, given a text T, a pattern P, and a threshold k,
the task is to find (the starting positions of) all substrings of T that are at distance at most k …

We study the classic Text-to-Pattern Hamming Distances problem: given a pattern P of
length m and a text T of length n, both over a polynomial-size alphabet, compute the …

Longest Common Substring (LCS) is an important text processing problem, which has
recently been investigated in the quantum query model. The decision version of this …

Computing the distance between a given pattern of length n and a text of length m is defined
as calculating, for every m-substring of the text, the distance between the pattern and the …

In this work, we revisit the fundamental and well-studied problem of approximate pattern
matching under edit distance. Given an integer k, a pattern P of length m, and a text T of …

Can we analyze data without decompressing it? As our data keeps growing, understanding
the time complexity of problems on compressed inputs, rather than in convenient …

We consider the streaming complexity of a fundamental task in approximate pattern
matching: the k-mismatch problem. In this problem, we must compute Hamming distances …

We revisit a fundamental problem in string matching: given a pattern of length m and a text of
length n, both over an alphabet of size σ, compute the Hamming distance (ie, the number of …

We consider approximate circular pattern matching (CPM, in short) under the Hamming and
edit distance, in which we are given a length-$ n $ text $ T $, a length-$ m $ pattern $ P …