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Record W4238222639 · doi:10.1145/354222.353194

An Aristotelian understanding of object-oriented programming

2000· article· en· W4238222639 on OpenAlexaff
Derek Rayside, Gerard T. Campbell

Bibliographic record

VenueACM SIGPLAN Notices · 2000
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsSt. Jerome's UniversityUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceObject (grammar)Predicate (mathematical logic)Programming languageLogic programmingObject-oriented programmingProgramming paradigmFirst-order logicRelation (database)Inductive programmingEpistemologyArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

The folklore of the object-oriented programming community at times maintains that object-oriented programming has drawn inspiration from philosophy, specifically that of Aristotle. We investigate this relation, first of all, in the hope of attaining a better understanding of object-oriented programming and, secondly, to explain aspects of Aristotelian logic to the computer science research community (since it differs from first order predicate calculus in a number of important ways). In both respects we endeavour to contribute to the theory of objects, albeit in a more philosophical than mathematical fashion.

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 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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.036
GPT teacher head0.289
Teacher spread0.253 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations8
Published2000
Admission routes1
Has abstractyes

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