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Sound Over-Approximation of Equational Reasoning with Variable-Preserving Rules Parameterized by Derivation Depth

AAAI 2025 · Learning theory and algorithms › Combinatorial and search optimization · approach: Logic and answer set programming theory · 0 citations (OpenAlex)

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Shows that ground equational reasoning with variable-preserving axioms can be soundly over-approximated in FPT time parameterized by derivation depth, via tree-automata completion.

Problem

Deciding whether a ground equation follows from a set of equational axioms is undecidable in general and NEXP-complete for depth bounded in binary; the paper targets tractable handling of bounded-depth parallel equational derivations.

Approach

Builds a tree automaton A(E,d,t) by iteratively applying a tree-automata completion step N(A,E) for each depth level, whose language soundly over-approximates terms reachable from t in d parallel rewriting steps; membership of t' in this language gives a YES/NO decision that is sound with respect to the equational closure.

Key results

Surprising findings

Limitations

Experimental setup

Builds on: Birkhoff's theorem tree automata completion multi-step rewriting (van Oostrom)

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