Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 269

The DOI matches its Crossref record.

Modules for standard ML

Open access
MacQueen, David·1984·Proceedings of the 1984 ACM Symposium on LISP and functional programming - LFP '84

Abstract

The functional programming language ML has been undergoing a thorough redesign during the past year, and the module facility described here has been proposed as part of the revised language, now called Standard ML. The design has three main goals: (1) to facilitate the structuring of large ML programs; (2) to support separate compilation and generic library units; and (3) to employ new ideas in the semantics of data types to extend the power of ML's polymorphic type system. It is based on concepts inherent in the structure of ML, primarily the notions of a declaration, its type signature, and the environment that it denotes.

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 · 10.1145/800055.802036

Cites

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

Cited by

See all 269

Metadata

Authors
MacQueen, D.
Venue
Proceedings of the 1984 ACM Symposium on LISP and functional programming - LFP '84
Publisher
ACM Press
Published
1984
Pages
198-207
OpenAlex
W2099305192
Cited by
269
References
0
FWCI
8.16
Type
conference paper
Language
en
Open access
gold

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: Modules for standard ML. https://app.cochat.ai/papers/10.1145/800055.802036
The paper
MacQueen, D. (1984). Modules for standard ML. Proceedings of the 1984 ACM Symposium on LISP and functional programming - LFP '84. https://doi.org/10.1145/800055.802036

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.