MétaCan
Menu
Back to cohort
Record W4412989191 · doi:10.1145/3747519

Fusing Session-Typed Concurrent Programming into Functional Programming

2025· article· en· W4412989191 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 · 2025
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversité du Québec à MontréalMcGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceSession (web analytics)Programming languageFunctional reactive programmingFunctional logic programmingProgramming paradigmInductive programmingWorld Wide Web

Abstract

fetched live from OpenAlex

We introduce FuSes , a Fu nctional programming language that integrates Ses sion-typed concurrent process calculus code. A functional layer sits on top of a session-typed process layer. To generate and reason about open session-typed processes, the functional layer uses the contextual box modality extended with linear channel contexts. Due to the fundamental differences between the operational semantics of the functional layer and the concurrent semantics of processes, we bridge the two layers using a set of primitives to run and observe the behavior of closed processes within the functional layer. In addition, FuSes supports code analysis and manipulation of open session-typed process code. To showcase its benefit to programmers, we implement well-known optimizations, such as batch optimizations, as type-safe metaprograms over concurrent processes. Our technical contributions include a type system for FuSes , an operational semantics, a proof of its type safety, and an 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0040.002
Research integrity0.0000.001
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 head0.021
GPT teacher head0.285
Teacher spread0.265 · 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