Measuring the dynamic behaviour of AspectJ programs
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
This paper proposes and implements a rigorous method for studying the dynamic behaviour of AspectJ programs. As part of this methodology several new metrics specific to AspectJ programs are proposed and tools for collecting the relevant metrics are presented. The major tools consist of: (1) a modified version of the AspectJ compiler that tags bytecode instructions with an indication of the cause of their generation, such as a particular feature of AspectJ; and (2) a modified version of the *J dynamic metrics collection tool which is composed of a JVMPI-based trace generator and an analyzer which propagates tags and computes the proposed metrics. This dynamic propagation is essential, and thus this paper contributes not only new metrics, but also non-trivial ways of computing them. We furthermore present a set of benchmarks that exercise a wide range of AspectJ's features, and the metrics that we measured on these benchmarks. The results provide guidance to AspectJ users on how to avoid efficiency pitfalls, to AspectJ implementors on promising areas for future optimization, and to tool builders on ways to understand the runtime behaviour of AspectJ.
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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 | 0.001 |
| 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 | 0.002 | 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