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Record W2026691974 · doi:10.1016/j.entcs.2006.10.036

Type-Safe Code Transformations in Haskell

2007· article· en· W2026691974 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.

Bibliographic record

VenueElectronic Notes in Theoretical Computer Science · 2007
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsProgramming languageHaskellComputer scienceCompilerAbstract syntaxDependent typeCorrectnessType (biology)Transformation (genetics)Type inferenceFunctional programmingTheoretical computer scienceSemantics (computer science)Lambda calculusInferenceArtificial intelligence

Abstract

fetched live from OpenAlex

The use of typed intermediate languages can significantly increase the reliability of a compiler. By type-checking the code produced at each transformation stage, one can identify bugs in the compiler that would otherwise be much harder to find. We propose to take the use of types in compilation a step further by verifying that the transformation itself is type correct, in the sense that it is impossible that it produces an ill typed term given a well typed term as input. We base our approach on higher-order abstract syntax (HOAS), a representation of programs where variables in the object language are represented by meta-variables. We use a representation that accounts for the object language's type system using generalized algebraic data types (GADTs). In this way, the full binding and type structure of the object language is exposed to the host language's type system. In this setting we encode a type preservation property of a CPS conversion in Haskell's type system, using witnesses of a type correctness proof encoded in a GADT.

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)0.004
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.965
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.011
GPT teacher head0.265
Teacher spread0.254 · 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