Deconstructing Subset Construction -- Reducing While Determinizing

Bibliographic Details
Title: Deconstructing Subset Construction -- Reducing While Determinizing
Authors: Nicol, John, Frohme, Markus
Publication Year: 2025
Collection: Computer Science
Subject Terms: Computer Science - Formal Languages and Automata Theory, Computer Science - Machine Learning
Description: We present a novel perspective on the NFA canonization problem, which introduces intermediate minimization steps to reduce the exploration space on-the-fly. Essential to our approach are so-called equivalence registries which manage information about equivalent states and allow for incorporating further optimization techniques such as convexity closures or simulation to boost performance. Due to the generality of our approach, these concepts can be embedded in classic subset construction or Brzozowski's approach. We evaluate our approach on a set of real-world examples from automatic sequences and observe that we are able to improve especially worst-case scenarios. We implement our approach in an open-source library for users to experiment with.
Comment: 19 pages, 2 figures
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2505.10319
Accession Number: edsarx.2505.10319
Database: arXiv
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