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Record W2156029045 · doi:10.15866/irecos.v8i3.3176

A MDA-Based Model-Driven Approach to Generate GUI for Mobile Applications

2013· article· en· W2156029045 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 Review on Computers and Software (IRECOS) · 2013
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsComputer scienceUnified Modeling LanguageGraphical user interfaceModel driven developmentCode generationModel transformationAndroid (operating system)Programming languageUser interfaceClass diagramSoftware engineeringEmbedded systemOperating systemSoftwareArtificial intelligence

Abstract

fetched live from OpenAlex

Developing applications for mobile platforms is a compound task, due to variability of mobile OSs and the number of different devices that need to be supported. Model-Driven Architecture (MDA) approach could provide a possible solution to offer an automated way to generate a Graphical User Interface (GUI) for such applications. In this paper, we propose a MDA-based model-driven approach to generate the GUI for mobile applications. The adopted approach consists of four main steps (i) modeling the GUI under UML; (ii) transforming the obtained diagrams to a simplified XMI schema; (iii) model-to-model transformation; and (iv) model-to-code generation. Our method has the advantages to give a graphical way for designing under UML. Currently, the method has been implemented to support two platforms Android and BlackBerry. The applicability of the approach is demonstrated via a case study that illustrates the GUI code generation for mobile platforms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.272
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