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Record W4405809911 · doi:10.1017/s0956796824000121

A simple blame calculus for explicit nulls

2024· article· en· W4405809911 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

VenueJournal of Functional Programming · 2024
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBlameComputer scienceType (biology)Calculus (dental)Function (biology)Simple (philosophy)Programming languageNull (SQL)Algebra over a fieldMathematicsPure mathematicsPhilosophyEpistemology

Abstract

fetched live from OpenAlex

Abstract Gradual typing provides a model for when a legacy language with less precise types interacts with a newer language with more precise types. Casts mediate between types of different precision, allocating blame when a value fails to conform to a type. The blame theorem asserts that blame always falls on the less-precisely typed side of a cast. One instance of interest is when a legacy language (such as Java) permits null values at every type, while a newer language (such as Scala or Kotlin) explicitly indicates which types permit null values. Nieto et al. in 2020 introduced a gradually typed calculus for just this purpose. The calculus requires three distinct constructors for function types and a non-standard proof of the blame theorem; it can embed terms from the legacy language into the newer language (or vice versa) only when they are closed. Here, we define a simpler calculus that is more orthogonal, with one constructor for function types and one for possibly nullable types, and with an entirely standard proof of the blame theorem; it can embed terms from the legacy language into the newer language (and vice versa) even if they are open. All results in the paper have been mechanized in Coq.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.631

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.037
GPT teacher head0.280
Teacher spread0.243 · 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