Cited by 739Logic, Reasoning, and KnowledgeAdvanced Graph Theory ResearchLogic, programming, and type systems

Complexity and expressive power of logic programming

Dantsin, Evgeny, Eiter, Thomas, Gottlob, Georg, Voronkov, Andrei·2001·ACM Computing Surveys

Abstract

This article surveys various complexity and expressiveness results on different forms of logic programming. The main focus is on decidable forms of logic programming, in particular, propositional logic programming and datalog, but we also mention general logic programming with function symbols. Next to classical results on plain logic programming (pure Horn clause programs), more recent results on various important extensions of logic programming are surveyed. These include logic programming with different forms of negation, disjunctive logic programming, logic programming with equality, and constraint logic programming.

Integrity signals

Registry

Crossref · 10.1145/502807.502810

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Compared to definite programs, the main advantage of Datalog is decidability.

    “Compared to definite programs, the main advantage of Datalog is decidability (Dantsin et al., 2001).”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Dantsin et al., 2001

Cited by

Sorted by citations

Authors
Dantsin, E., Eiter, T., Gottlob, G., & Voronkov, A.
Affiliations
  • Roosevelt University (US)
  • TU Wien (AT)
  • University of Manchester, Manchester, United Kingdom
Venue
ACM Computing Surveys
Published
2001-09
Volume
33
Issue
3
Pages
374-425
ISSN
  • 0360-0300 (ISSN-L)
  • 1557-7341
OpenAlex
W1969965298
Cited by
739
References
0
Citations by year
2026: 11 · 2025: 11 · 2024: 17 · 2023: 22 · 2022: 25 · 2021: 29 · 2020: 21 · 2019: 30 · 2018: 27 · 2017: 30 · 2016: 30 · 2015: 28 · 2014: 45 · 2013: 41 · 2012: 39
FWCI
24.49
Type
journal article
Language
en
Open access
closed
Locations
  • ACM Computing Surveys (publishedVersion)
  • Research Explorer (The University of Manchester) (submittedVersion, public-domain)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Graph Theory Research
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, programming, and type systems
Keywords
logic programming, computational complexity, expressiveness, Datalog, negation, disjunctive logic programming, constraint logic programming, function symbols

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review