Object-Oriented Fixpoint Programming with Datalog

Modern usages of Datalog exceed its original design purpose in scale and complexity. In particular, Datalog lacks abstractions for code organization and reuse, making programs hard to maintain. Is it possible to exploit abstractions and design patterns from object-oriented programming (OOP) while retaining a Datalog-like fixpoint semantics? To answer this question, we design a new OOP language called OODL with common OOP features: dynamic object allocation, object identity, dynamic dispatch, and mutation. However, OODL has a Datalog-like fixpoint semantics, such that recursive computations iterate until their result becomes stable. We develop two semantics for OODL: a fixpoint interpreter and a compiler that translates OODL to Datalog. Although the side effects found in OOP (object allocation and mutation) conflict with Datalog's fixpoint semantics, we can mostly resolve these incompatibilities through extensions of OODL. Within fixpoint computations, we employ immutable algebraic data structures (e.g. case classes in Scala), rather than relying on object allocation, and we introduce monotonically mutable data types ( mono types ) to enable a relaxed form of mutation. Our performance evaluation shows that the interpreter fails to solve fixpoint problems efficiently, whereas the compiled code exploits Datalog's semi-naïve evaluation.

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Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2024-10-08
DOI
https://doi.org/10.1145/3689713
Citations
2
Primary Topic
Logic, programming, and type systems
Type
article
Field-Weighted Citation Impact
0.69
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article

Object-Oriented Fixpoint Programming with Datalog

Sebastian Erdweg, D. A. Klopp, André Pacak
2 citations
Proceedings of the ACM on Programming Languages
Logic, programming, and type systems
0.69
article

Object-Oriented Fixpoint Programming with Datalog

Sebastian Erdweg, D. A. Klopp, André Pacak
article en
2 citations

Abstract

Modern usages of Datalog exceed its original design purpose in scale and complexity. In particular, Datalog lacks abstractions for code organization and reuse, making programs hard to maintain. Is it possible to exploit abstractions and design patterns from object-oriented programming (OOP) while retaining a Datalog-like fixpoint semantics? To answer this question, we design a new OOP language called OODL with common OOP features: dynamic object allocation, object identity, dynamic dispatch, and mutation. However, OODL has a Datalog-like fixpoint semantics, such that recursive computations iterate until their result becomes stable. We develop two semantics for OODL: a fixpoint interpreter and a compiler that translates OODL to Datalog. Although the side effects found in OOP (object allocation and mutation) conflict with Datalog's fixpoint semantics, we can mostly resolve these incompatibilities through extensions of OODL. Within fixpoint computations, we employ immutable algebraic data structures (e.g. case classes in Scala), rather than relying on object allocation, and we introduce monotonically mutable data types ( mono types ) to enable a relaxed form of mutation. Our performance evaluation shows that the interpreter fails to solve fixpoint problems efficiently, whereas the compiled code exploits Datalog's semi-naïve evaluation.

Proceedings of the ACM on Programming LanguagesVol. 8(OOPSLA2)
Openalex Percentile: Top 24%
Logic, programming, and type systems
0.69
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Object-Oriented Fixpoint Programming with Datalog — Sebastian Erdweg, D. A. Klopp, et al. · Proceedings of the ACM on Programming Languages (2024) | TGRS Research Map | TGRS