Proceedings of the 6th international conference on Aspect-oriented software development
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.035 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".