EDBT 2026 Demo / reviewers in the wild / expert
Peter Van Weert
dblp:37/6037
· DBLP profile ↗
7ranked-venue papers
4as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 5 · 3 first-authorTheory of computation · 4 · 3 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author
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% Compilers and program optimization · 44% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems › programming paradigms
rule-based programming |
0.1 | 1 | 2010 | Efficient Lazy Evaluation of Rule-Based Programs · IEEE Trans. Knowl. Data Eng. 2010 |
Methods — techniques the papers use, named apart from their topics
rete algorithm · 0.1TREAT algorithm · 0.1LEAPS algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Efficient Lazy Evaluation of Rule-Based ProgramsabstractThirty years after Forgy's seminal dissertation, Rete remains the de facto standard matching algorithm. Despite promising research results, alternative algorithms such as TREAT and LEAPS have had little impact on modern production rule engines. Constraint Handling Rules (CHR) is a high-level, declarative programming language, similar to production rules. In recent years, CHR has increasingly been used in a wide range of general purpose applications. State-of-the-art CHR systems use LEAPS-like lazy matching, and implement a large body of novel program analyses and optimization techniques to further improve performance. While obviously related, CHR and production rules research have mostly evolved independently from each other. With this paper, we aim to foster cross fertilization of implementation techniques. We provide a lucid, comprehensive overview of CHR's rule evaluation methodology, and survey recent contributions to the field of lazy matching. Our empirical evaluation confirms that Rete-based engines would surely benefit from incorporating similar techniques and optimizations. Peter Van Weert |
IEEE Trans. Knowl. Data Eng. | 1 |
| 2010 | As time goes by: Constraint Handling RulesabstractAbstract Constraint Handling Rules (CHR) is a high-level programming language based on multiheaded multiset rewrite rules. Originally designed for writing user-defined constraint solvers, it is now recognized as an elegant general purpose language. Constraint Handling Rules related research has surged during the decade following the previous survey by Frühwirth (J. Logic Programming, Special Issue on Constraint Logic Programming, 1998, vol. 37, nos. 1–3, pp. 95–138). Covering more than 180 publications, this new survey provides an overview of recent results in a wide range of research areas, from semantics and analysis to systems, extensions, and applications. Jon Sneyers, Peter Van Weert, Tom Schrijvers, Leslie De Koninck |
Theory Pract. Log. Program. | 2 |
| 2008 | Actors with Multi-headed Message Receive Patterns
Martin Sulzmann, Edmund Soon Lee Lam, Peter Van Weert |
COORDINATION | 3 |
| 2008 | Optimization of CHR Propagation Rules
Peter Van Weert |
ICLP | 1 |
| 2007 | Aggregates in Constraint Handling Rules
Jon Sneyers, Peter Van Weert, Tom Schrijvers, Bart Demoen |
ICLP | 2 |
| 2007 | Extension and Implementation of CHR
Peter Van Weert |
ICLP | 1 |
| 2007 | Aggregates for CHR through Program Transformation
Peter Van Weert, Jon Sneyers, Bart Demoen |
LOPSTR | 1 |