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Record W1917056660 · doi:10.1109/ccece.1995.526606

COP: a simple way to integrate imperative programming and declarative programming

2002· article· en· W1917056660 on OpenAlexaff
Charles-Antoine Brunet, Ricardo Rubio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsProgramming languagePrologComputer scienceProgrammerFifth-generation programming languageLogic programmingDeclarative programmingProcedural programmingSyntaxSemantics (computer science)DatalogProgramming paradigmInductive programmingArtificial intelligence

Abstract

fetched live from OpenAlex

The paper proposes how to integrate two languages, C++ and Prolog, into one. The resulting language is COP (C++ Or Prolog). The motivation behind this work was to offer in one language two programming styles in order to simplify program writing. For example, an application programmer can use the COP language when it is necessary to program in a procedural or object oriented way (C++) and also with rules (Prolog). Our feeling is that a programmer could benefit from our approach because he or she has the choice to use a programming style adapted to the application needs. We present the COP language. In COP, we try to respect the syntax, the semantics and the philosophies of C++ and Prolog. We define how the two languages can work together. Our approach is to add some features allowing C++ to call Prolog goals. We give all the details that a COP programmer must know in order to use the language; that was possible because we kept our design as simple as we could.

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)0.003
metaresearch head score (Gemma)0.006
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.006
Open science0.0020.005
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0080.004

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 head0.033
GPT teacher head0.268
Teacher spread0.234 · 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
GenreMethods

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

Citations1
Published2002
Admission routes1
Has abstractyes

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