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Record W3037337664 · doi:10.3991/ijes.v8i2.14131

A Model Driven Approach for Generating Angular 7 Applications

2020· article· en· W3037337664 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

VenueInternational Journal of Recent Contributions from Engineering Science & IT (iJES) · 2020
Typearticle
Languageen
FieldComputer Science
TopicWeb Applications and Data Management
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsClass diagramCode generationCode (set theory)Unified Modeling LanguageComputer scienceGenerator (circuit theory)Class (philosophy)DiagramUse Case DiagramProgramming languageActivity diagramSoftware engineeringArtificial intelligenceSoftwareDatabaseComputer securitySet (abstract data type)Power (physics)

Abstract

fetched live from OpenAlex

The proliferation of language and framework updates and the appearance of new ones has made the need for code generation tools an inescapable one. For this reason, many companies have started to invest in this area with the aim of perpetuating the sssknow-how.MDA-Model Driven Architecture- has enabled semi-automatic generation of code via models. The MOFM2T standard is independent of the generated language, but to date, no generator of Angular code from a UML diagram has never seen the light of day, the objective of this article is to propose a platform allowing from a class diagram to generate an operational application in Angular 7.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.377
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
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 head0.026
GPT teacher head0.277
Teacher spread0.252 · 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