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Record W2913303161

Proceedings of the 13th workshop on Aspect-oriented modeling

2009· article· en· W2913303161 on OpenAlexaff
Omar Aldawud, Walter Cazzola, Thomas Cottenier, Jeff Gray, Jörg Kienzle, Dominik Stein

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsAspect-oriented programmingSoftware engineeringComputer scienceSoftwareModeling languageAbstractionPerspective (graphical)EngineeringProgramming languageArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

New and powerful aspect-oriented programming techniques are presented at many international venues every year. However, it is not clear what features of such techniques are common aspect-oriented concepts and what features are rather language-specific specialties. Research in aspect-oriented modeling has the potential to help find such common characteristics from a perspective that is at a more abstract level (i.e., programming language-independent). The Aspect-Oriented Modeling (AOM) Workshops, now in its 13th edition, bring together researchers and practitioners from two communities: aspect-oriented software development (AOSD) and software model engineering. The workshops provide a forum for presenting new ideas and discussing the state of research and practice in modeling various kinds of crosscutting concerns at different levels of abstraction. The goals of the workshops are to identify and discuss the impacts of aspect-oriented technologies on model engineering. Specifically, the workshop seeks to provide aspect-oriented software developers with general modeling means to express aspects and their crosscutting relationships onto other software artifacts. The aspect-oriented modeling workshops occur twice a year as satellite events of the AOSD and MoDELS conferences. These workshops receive a strong following among researchers in both communities with activie participation that has helped to unite these two areas over the past seven years. More details are available at: http://www.aspect-modeling.org.

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 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)0.001
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 score0.448
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.041
GPT teacher head0.284
Teacher spread0.244 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2009
Admission routes1
Has abstractyes

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