MétaCan
Menu
Back to cohort
Record W2156154755 · doi:10.1145/638750.638778

A brief history of the object-oriented approach

2003· article· en· W2156154755 on OpenAlexaff
Luiz Fernando Capretz

Bibliographic record

VenueACM SIGSOFT Software Engineering Notes · 2003
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsWestern University
Fundersnot available
KeywordsComputer scienceObject-oriented programmingSoftware developmentSoftware engineeringObject (grammar)SoftwareProgramming languageArtificial intelligence

Abstract

fetched live from OpenAlex

Unlike other fads, the object-oriented paradigm is here to stay. The road towards an object-oriented approach is described and several object-oriented programming languages are reviewed. Since the object-oriented paradigm promised to revolutionize software development, in the 1990s, demand for object-oriented software systems increased dramatically; consequently, several methodologies have been proposed to support software development based on that paradigm. Also presented are a survey and a classification scheme for object oriented methodologies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.007
Science and technology studies0.0020.003
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.013

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 head0.017
GPT teacher head0.198
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueACM SIGSOFT Software Engineering NotesSame topicLogic, programming, and type systemsFrench-language works237,207