Proceedings of the tenth international conference on Aspect-oriented software development companion
Bibliographic record
Abstract
It is our great pleasure to welcome you to the 10th International Conference on Aspect-Oriented Software Development (AOSD), for the first time in Brazil. AOSD is the premier forum for presentation of research results and experience reports on software modularity, with an emphasis on modular structures that cut across traditional abstraction boundaries. The annual AOSD series started in 2002 in Enschede (The Netherlands), followed by Boston, Massachusetts (USA) in 2003, Lancaster (UK) in 2004, Chicago, Illinois (USA) in 2005, Bonn (Germany) in 2006, Vancouver (Canada) in 2007, Brussels (Belgium) in 2008, Charlottesville, Virginia (USA) in 2009, Rennes and Saint-Malo (France) in 2010, and Porto de Galinhas in 2011. This year's conference continues the tradition of its successful predecessors with Research and Industry Tracks, which bring together leading researchers and practitioners working in such fields as software engineering, programming languages, systems, and others. Besides these tracks, this year we have the satisfaction of introducing the Modularity Visions Track, which aims to think about modularity for the future, and hosting an ACM SIGPLAN Student Research Competition. Finally, to celebrate AOSD's 10th birthday, we have a special Retrospective on Modularity session and an outstanding group of keynote and invited speakers. In this way we hope to continue broadening its scope with respect to software developments activities, and start broadening the scope with respect to other advanced modularization mechanisms beyond aspects.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.124 | 0.078 |
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".