Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 231

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Set-oriented production rules in relational database systems

Open access
Widom, Jennifer, Finkelstein, S. J.·1990·Proceedings of the 1990 ACM SIGMOD international conference on Management of data

Abstract

We propose incorporating a production rules facility into a relational database system. Such a facility allows definition of database operations that are automatically executed whenever certain conditions are met. In keeping with the set-oriented approach of relational data manipulation languages, our production rules are also set-oriented—they are triggered by sets of changes to the database and may perform sets of changes. The condition and action parts of our production rules may refer to the current state of the database as well as to the sets of changes triggering the rules. We define a syntax for production rule definition as an extension to SQL. A model of system behavior is used to give an exact semantics for production rule execution, taking into account externally-generated operations, self-triggering rules, and simultaneous triggering of multiple rules.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/93597.98735

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 231

Metadata

Authors
Widom, J., & Finkelstein, S. J.
Venue
Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Publisher
ACM
Published
1990-05
Pages
259-270
ISSN
0730-8078 (ISSN-L)
OpenAlex
W2056947248
Cited by
231
References
1
FWCI
19.02
Type
conference paper
Language
en
Open access
bronze

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

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Set-oriented production rules in relational database systems. https://app.cochat.ai/papers/10.1145/93597.98735
The paper
Widom, J., & Finkelstein, S. J. (1990). Set-oriented production rules in relational database systems. Proceedings of the 1990 ACM SIGMOD international conference on Management of data. https://doi.org/10.1145/93597.98735

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.