Year: 2026
Type: article
Abstract: Given an unsatisfiable formula, understanding the core reason for unsatisfiability is crucial in several applications. One effective way to capture this is through the minimal unsatisfiable subset (MUS), the subset-minimal set of clauses that remains unsatisfiable. Current research broadly focuses on two directions: (i) enumerating as many MUSes as possible within a given time limit, and (ii) counting the total number of MUSes for a given unsatisfiable formula. In this paper, we introduce an answer set programming-based framework, named MUS-ASP, designed for online enumeration of MUSes. ASP is a powerful tool for its strengths in knowledge representation and is particularly suitable for specifying complex combinatorial problems. By translating MUS enumeration into answer set solving, MUS-ASP leverages the computational efficiency of state-of-the-art ASP systems. Our extensive experimental evaluation demonstrates the effectiveness of MUS-ASP and highlights the acceleration in both MUS enumeration and counting tasks, particularly when integrated within hybrid solvers, including the framework proposed in this paper.
DOI: 10.4204/eptcs.439.3
Authors: Mohimenul Kabir, Kuldeep S Meel
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415345332
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