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Record W1565619322

OO-IP hybrid language design and a framework approach to the GIPC

2009· dissertation· en· W1565619322 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

VenueSpectrum Research Repository (Concordia University) · 2009
Typedissertation
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsProgramming languageComputer scienceProgramming paradigmCompilerGeneric programmingModularity (biology)Fifth-generation programming languageMetaprogrammingVery high-level programming languageProcedural programmingJavaFirst-generation programming languageFunctional logic programmingInductive programming
DOInot available

Abstract

fetched live from OpenAlex

Intensional Programming is a declarative programming paradigm in which expressions are evaluated in an inherently multidimensional context space. The Lucid family of programming languages is, to this day, the only programming languages of true intensional nature. Lucid being a functional language, Lucid programs are inherently parallel and their parallelism can be efficiently exploited by the adjunction of a procedural language to increase the granularity of its parallelism, forming hybrid Lucid languages. That very wide array of possibilities raises the need for an extremely flexible programming language investigation platform to investigate on this plethora of possibilities for Intensional Programming. That is the purpose of the General Intensional Programming System (GIPSY), especially, the General Intensional Programming Compiler (GIPC) component. The modularity, reusability and extensibility aspects of the framework approach make it an obvious candidate for the development of the GIPC. The framework presented in this thesis provides a better solution compared to all other techniques used to this day to implement the different variants of intensional programming. Because of the functionality of hybrid programming support in the GIPC framework, a new OO-IP hybrid language is designed for further research. This new hybrid language combines the essential characteristics of IPL and Java, and introduces the notion of object streams which makes it is possible that each element in an IPL stream could be an object with embedded intensional properties. Interestingly, this hybrid language also brings to Java objects the power which can explicitly express context, creating the novel concept of intensional objects, Le. objects whose evaluation is context-dependent, which are therein demonstrated to be translatable into standard objects. By this new feature, we extend the use and meaning of the notion of object and enrich the meaning of stream in IPL and semantics of Java. At the same time, during the procedure to introduce intensional objects and this OO-IP hybrid language, many factors are considered. These factors include how to integrate the new language with the GIPC framework design and the issues related to its integration in the current GIPSY implementation. Current semantic rules show that the new language can work well with the GIPC framework and the GIPSY implementation, which is another proof of the validity of our GIPC framework design. Ultimately, the proposed design is put into implementation in the GIPSY and the implementation put to test using programs from different application domains written in this new OO-IP language

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.391
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.002
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 head0.044
GPT teacher head0.306
Teacher spread0.262 · 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