Efficient POSIX submatch extraction on nondeterministic finite automata

In this paper we study the performance of POSIX submatch extraction algorithms based on nondeterministic finite automata (NFA). We propose an algorithm that combines Laurikari tagged NFA and extended Okui-Suzuki disambiguation. The algorithm works in worst-caseO(n m(2) t)time andO(m(2))space (including preprocessing), wherenis the length of input,mis the size of the regular expression with bounded repetition expanded andtis the number of capturing groups and subexpressions that contain them. On real-world benchmarks our algorithm performs close to theO(n m t)complexity of leftmost-greedy matching, although on artificial benchmarks it can be significantly slower. We propose a lazy version of the algorithm that runs much faster, but requiresO(n m(2))space. We show that the Kuklewicz algorithm is slower in practice, and the backward matching algorithm proposed by Cox is incorrect.