Faster Approximate String Matching for Short Patterns

We study the classical approximate string matching problem, that is, given strings $P$ and $Q$ and an error threshold $k$, find all ending positions of substrings of $Q$ whose edit distance to $P$ is at most $k$. Let $P$ and $Q$ have lengths $m$ and $n$, respectively. On a standard unit-cost word RAM with word size $w \geq \log n$ we present an algorithm using time $$ O(nk \cdot \min(\frac{\log² m}{\log n},\frac{\log² m\log w}{w}) + n) $$ When $P$ is short, namely, $m = 2^{{o(\sqrt{\log} n})}$ or $m = 2^{{o(\sqrt{w/\log} w})}$ this improves the previously best known time bounds for the problem. The result is achieved using a novel implementation of the Landau-Vishkin algorithm based on tabulation and word-level parallelism.