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Record W184528236

Proceedings of the 6th international conference on Aspect-oriented software development

2007· article· en· W184528236 on OpenAlexaff
Brian Barry

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsBC Research (Canada)
Fundersnot available
KeywordsComputer sciencePresentation (obstetrics)Software engineeringModularity (biology)Theme (computing)AbstractionSoftware developmentSoftwareProgramming languageWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

AOSD is the premier conference on software modularity, with an emphasis on novel notions of modularity that crosscut traditional abstraction boundaries. The AOSD research track brings together leading researchers and practitioners working in the fields of software engineering, programming languages, and software systems. This volume consists of the papers presented in that research track at the 6th edition of AOSD, in 2007.A total of 107 papers were submitted, and 361 in-depth technical reviews were produced to rank the papers according to quality; many of the strong contenders received five reviews or more. Authors had an opportunity to respond to reviews, and this helped clear up some misunderstandings. The research program committee then met in Oxford to make the final selection of 19 papers. The program reflects how AOSD brings together different communities around the theme of crosscutting concerns:Several papers on applications demonstrate both the need for aspect-orientation, and how current technologies meet that need.A continuing theme at AOSD is the use of aspects at the design stage, along with tools that assist with a transition to code. There is also a session on tools more generally, for instance to bring out crosscutting concerns in the presentation of code.AOSD always has strong input from the programming language community and this year is no exception. A new perspective for 2007 is provided by several papers on programming language semantics, which present mathematical theories for reasoning about aspects (a long-standing open issue), and to guide the design of new aspect-oriented programming languages.Finally, we have a strong session on finding crosscutting concerns in existing code.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.864
Threshold uncertainty score0.257

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 head0.046
GPT teacher head0.294
Teacher spread0.249 · 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 designTheoretical or conceptual
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
Published2007
Admission routes1
Has abstractyes

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