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Breaking the Negative Cycle: Exploring the Design Space of Stratification for First-Class Datalog Constraints

Authors Jonathan Lindegaard Starup , Magnus Madsen , Ondřej Lhoták

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ACM Subject Classification
  • Theory of computation → Constraint and logic programming
Keywords
  • Datalog
  • first-class Datalog constraints
  • negation
  • stratified negation
  • type system
  • row polymorphism
  • the Flix programming language

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Abstract

The λ_Dat calculus brings together the power of functional and declarative logic programming in one language. In λ_Dat, Datalog constraints are first-class values that can be constructed, passed around as arguments, returned, composed with other constraints, and solved.
A significant part of the expressive power of Datalog comes from the use of negation. Stratified negation is a particularly simple and practical form of negation accessible to ordinary programmers. Stratification requires that Datalog programs must not use recursion through negation.
For a Datalog program, this requirement is straightforward to check, but for a λ_Dat program, it is not so simple: A λ_Dat program constructs, composes, and solves Datalog programs at runtime. Hence stratification cannot readily be determined at compile-time.
In this paper, we explore the design space of stratification for λ_Dat. We investigate strategies to ensure, at compile-time, that programs constructed at runtime are guaranteed to be stratified, and we argue that previous design choices in the Flix programming language have been suboptimal.

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Jonathan Lindegaard Starup, Magnus Madsen, and Ondřej Lhoták. Breaking the Negative Cycle: Exploring the Design Space of Stratification for First-Class Datalog Constraints. In 37th European Conference on Object-Oriented Programming (ECOOP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 263, pp. 31:1-31:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.ECOOP.2023.31

Author Details

Jonathan Lindegaard Starup
  • Department of Computer Science, Aarhus University, Denmark
Magnus Madsen
  • Department of Computer Science, Aarhus University, Denmark
Ondřej Lhoták
  • David R. Cheriton School of Computer Science, University of Waterloo, Canada

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