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Record W1965418329 · doi:10.1145/1018203.1018208

A semantics for advice and dynamic join points in aspect-oriented programming

2004· article· en· W1965418329 on OpenAlexaff
Mitchell Wand, Gregor Kiczales, Christopher Dutchyn

Bibliographic record

VenueACM Transactions on Programming Languages and Systems · 2004
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceJoin (topology)Programming languageSemantics (computer science)Advice (programming)Aspect-oriented programmingDenotational semanticsCorrectnessSet (abstract data type)Operational semanticsSoftwareMathematics

Abstract

fetched live from OpenAlex

A characteristic of aspect-oriented programming, as embodied in Aspect J, is the use of advice and point cuts to define behavior that crosscuts the structure of the rest of the code. The events during execution at which advice may execute are called join points . A pointcut is a set of join points. An advice is an action to be taken at the join points in a particular pointcut. In this model of aspect-oriented programming, join points are dynamic in that they refer to events during the flow of execution of the program.We give a denotational semantics for a minilanguage that embodies the key features of dynamic join points, pointcuts, and advice. This is the first semantics for aspect-oriented programming that handles dynamic join points and recursive procedures. It is intended as a baseline semantics against which future correctness results may be measured.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.006
Scholarly communication0.0040.007
Open science0.0020.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.310
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations229
Published2004
Admission routes1
Has abstractyes

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