A semantics for advice and dynamic join points in aspect-oriented programming
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it