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Jonas Barklund

dblp:44/2238 · DBLP profile ↗
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11ranked-venue papers
6as first author
0since 2021 · last 2000
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 7 · 5 first-authorSoftware engineering, systems software and programming languages · 4 · 4 first-authorDatabases, data management, data science and information retrieval · 4Artificial intelligence and machine learning · 3 · 1 first-authorSystems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Programming languages and type systems · 56% Runtime systems and virtual machines · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Runtime systems and virtual machines › interpreter
interpreter implementation
0.011987
Efficient interpretation of Prolog programs · PLDI 1987
Programming languages and type systems
logic programming
0.011987
Efficient interpretation of Prolog programs · PLDI 1987

Methods — techniques the papers use, named apart from their topics

meta-interpretation · 0.0
YearPublicationVenuePosition
2000 Reflection principles in computational logic
abstract
We introduce the concept of reflection principle as a knowledge representation paradigm in a computational logic setting. Reflection principles are expressed as certain kinds of logic schemata intended to capture the basic properties of the domain knowledge to be modelled. Reflection is then used to instantiate these schemata to answer specific queries about the domain. This differs from other approaches to reflection mainly in the following three ways. First, it uses logical instead of procedural reflection. Second, it aims at a cognitively adequate declarative representation of various forms of knowledge and reasoning, as opposed to reflection as a means for controlling computation or deduction. Third, it facilitates the building of a complex theory by allowing a simpler theory to be enhanced by a compact metatheory, contrary to the construction of metatheories that are only conservative extensions of the basic theory. A computational logic system for embedding reflection principles, called RCL (for Reflective Computational Logic), is presented in full detail. The system is an extension of Horn clause resolution-based logic, and is devised in a way that makes important features of reflection parametric as much as possible, so that they can be tailored according to specific needs of different application domains. Declarative and procedural semantics of the logic are described and correctness and completeness of reflection as logical inference are proved. Examples of reflection principles for three difference application areas are shown. Relationship with a variety of distinct sources within the literature on relevant topics is discussed.
Jonas Barklund, Pierangelo Dell'Acqua, Stefania Costantini, Gaetano Aurelio Lanzarone
J. Log. Comput.1
1996 On the Number of Edges in Cycletrees
Margus Veanes, Jonas Barklund
Inf. Process. Lett.2
1996 Construction of Natural Cycletrees
Margus Veanes, Jonas Barklund
Inf. Process. Lett.2
1996 Natural Cycletrees: Flexible Interconnection Graphs
Margus Veanes, Jonas Barklund
J. Parallel Distributed Comput.2
1995 Semantical Properties of SLD-Resolution with Reflection
Jonas Barklund, Pierangelo Dell'Acqua, Stefania Costantini, Gaetano Aurelio Lanzarone
ICLP1
1994 Reflection through Constraint Satisfaction
Jonas Barklund, Pierangelo Dell'Acqua, Stefania Costantini, Gaetano Aurelio Lanzarone
ICLP1
1993 Prolog with Arrays and Bounded Quantifications
Jonas Barklund, Johan Bevemyr
LPAR1
1990 Persistent Data Storage for Prolog
Monika Danielsson, Jonas Barklund
DEXA2
1990 An Intelligent Object Oriented Modelling to Legal Data Bases Combining Logic Programming and Hypertext
Andreas Hamfelt, Jonas Barklund
DEXA2
1987 Hash Tables in Logic Programming
Jonas Barklund, Håkan Millroth
ICLP1
1987 Efficient interpretation of Prolog programs
abstract
The paper focuses on three ideas for solving problems with writing interpreters for the logic programming language Prolog in Prolog and how to combine these ideas to an interpreter for Prolog which is both simple and efficient. The resulting interpreter system can be incorporated into a Prolog based on Warren's Abstract Machine and built mostly from existing parts of it. The interpreter has been implemented and is used in a Prolog system developed at Uppsala University.
Jonas Barklund
PLDI1