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Record W4386317102 · doi:10.1145/3607851

MacoCaml: Staging Composable and Compilable Macros

2023· article· en· W4386317102 on OpenAlexafffund
Ningning Xie, Leo White, Olivier Nicole, Jeremy Yallop

Bibliographic record

VenueProceedings of the ACM on Programming Languages · 2023
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversity of Toronto
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaIsaac Newton Trust
KeywordsComputer scienceCompilerProgramming languageMacroSoundnessCompile timePortingCode generationInterleavingOperating systemSoftware

Abstract

fetched live from OpenAlex

We introduce MacoCaml, a new design and implementation of compile-time code generation for the OCaml language. MacoCaml features a novel combination of macros with phase separation and quotation-based staging, where macros are considered as compile-time bindings, expression cross evaluation phases using staging annotations, and compile-time evaluation happens inside top-level splices. We provide a theoretical foundation for MacoCaml by formalizing a typed source calculus maco that supports interleaving typing and compile-time code generation, references with explicit compile-time heaps, and modules. We study various crucial properties including soundness and phase distinction. We have implemented MacoCaml in the OCaml compiler, and ported two substantial existing libraries to validate our implementation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.270
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the ACM on Programming LanguagesSame topicLogic, programming, and type systemsFrench-language works237,207