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Record W4386317102 · doi:10.1145/3607851

MacoCaml: Staging Composable and Compilable Macros

2023· article· en· W4386317102 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.555

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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