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Symmetric Linear Arc Monadic Datalog and Gadget Reductions

Authors Manuel Bodirsky , Florian Starke

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Manuel Bodirsky
  • Institut für Algebra, TU Dresden, Germany
Florian Starke
  • Institut für Algebra, TU Dresden, Germany

Funding

Both authors have been funded by the European Research Council (Project POCOCOP, ERC Synergy Grant 101071674). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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Manuel Bodirsky and Florian Starke. Symmetric Linear Arc Monadic Datalog and Gadget Reductions. In 28th International Conference on Database Theory (ICDT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 328, pp. 13:1-13:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.ICDT.2025.13

Abstract

A Datalog program solves a constraint satisfaction problem (CSP) if and only if it derives the goal predicate precisely on the unsatisfiable instances of the CSP. There are three Datalog fragments that are particularly important for finite-domain constraint satisfaction: arc monadic Datalog, linear Datalog, and symmetric linear Datalog, each having good computational properties. We consider the fragment of Datalog where we impose all of these restrictions simultaneously, i.e., we study symmetric linear arc monadic (slam) Datalog. We characterise the CSPs that can be solved by a slam Datalog program as those that have a gadget reduction to a particular Boolean constraint satisfaction problem. We also present exact characterisations in terms of a homomorphism duality (which we call unfolded caterpillar duality), and in universal-algebraic terms (using known minor conditions, namely the existence of quasi Maltsev operations and k-absorptive operations of arity nk, for all n,k ≥ 1). Our characterisations also imply that the question whether a given finite-domain CSP can be expressed by a slam Datalog program is decidable.

Subject Classification

ACM Subject Classification
  • Theory of computation → Finite Model Theory
Keywords
  • Datalog
  • Gadget Reductions
  • Homomorphism Dualities
  • Minor Conditions

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