A Categorical Modeling Approach of Aspect-Oriented Systems
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.
Bibliographic record
Abstract
Aspect Oriented (AO) Technology is a post-object oriented technology emerged to overcome limitations of Object Oriented (OO) Technology, such as the cross-cutting concern problem. Aspect Oriented Programming (AOP) also offers modularity and traceability benefits. Yet, reasoning, specification, and verification of AO systems present unique challenges especially as such systems evolve over time. Consequently, formal modular reasoning of such systems is highly attractive as it enables tractable evolution, otherwise necessitating that the entire system be reexamined each time a component is changed or is added. Besides, the aspect interactions problem is an open issue in aspect-oriented area. To deal with this problem, we choose to use category theory (CT) and algebraic specification(AS) techniques. In this paper, we present an aspect-oriented modeling (AOM) approach and a weaving algorithm. Our approach is expressive and allows for formal modular reasoning.
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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 | 0.001 | 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