Complexity of regular abstractions of one-counter languages

TL;DR

This paper investigates the complexity of transforming one-counter automata into finite automata recognizing various language abstractions, providing new algorithms and complexity bounds for these transformations.

Contribution

It introduces polynomial and quasi-polynomial algorithms for constructing NFAs from one-counter automata for different abstractions, and establishes complexity bounds and completeness results.

Findings

Polynomial-time algorithms for upward and downward closures and Parikh images over fixed alphabets.

Quasi-polynomial time algorithms for Parikh images with variable alphabet size.

Existence of sub-exponential size NFAs for these abstractions remains unresolved.

Abstract

We study the computational and descriptional complexity of the following transformation: Given a one-counter automaton (OCA) A, construct a nondeterministic finite automaton (NFA) B that recognizes an abstraction of the language L(A): its (1) downward closure, (2) upward closure, or (3) Parikh image. For the Parikh image over a fixed alphabet and for the upward and downward closures, we find polynomial-time algorithms that compute such an NFA. For the Parikh image with the alphabet as part of the input, we find a quasi-polynomial time algorithm and prove a completeness result: we construct a sequence of OCA that admits a polynomial-time algorithm iff there is one for all OCA. For all three abstractions, it was previously unknown if appropriate NFA of sub-exponential size exist.