# A Congruence-based Perspective on Automata Minimization Algorithms

## TL;DR

This paper offers a new perspective on automata minimization by applying a congruence-based framework to analyze and compare existing algorithms for deriving minimal deterministic automata.

## Contribution

It introduces a congruence-based framework that provides novel insights into the relationships between established automata minimization methods.

## Key findings

- Reveals connections between different minimization algorithms
- Provides a unified theoretical framework for automata reduction
- Enhances understanding of automata equivalence relations

## Abstract

In this work we use a framework of finite-state automata constructions based on equivalences over words to provide new insights on the relation between well-known methods for computing the minimal deterministic automaton of a language.