Proceedings of the 1st international workshop on Software architectures and mobility
Bibliographic record
Abstract
It is our great pleasure to welcome you to the First International Workshop on Software Architectures and Mobility (SAM 2008). The theme of this year ICSE is Driving World Business, acknowledging the crucial role the engineering of software plays in a variety of sectors, from business to health care, from telecommunications to embedded systems. Mobility stands out as an orthogonal dimension to most of these application domains: consider, for example, the outburst of m-commerce applications, or the use of pervasive computing technologies to deliver healthcare services in the future. The goal of this workshop is to strengthen the cross-fertilization of advances from requirements and domain engineering, software architectures, and middleware to systematically develop and evolve architectures supporting mobility. SAM gives software engineering researchers and practitioners a unique opportunity to facilitate information exchange, share ideas, and promote collaboration. The call for papers attracted both full and short papers from researchers in Asia, Canada, Europe and the United States. The program committee conducted a rigorous reviewing process, at the end of which 6 full papers and 6 short papers were accepted for presentation and discussion at the workshop. In addition, the program includes a keynote speech by Nenad Medvidović, from the University of Southern California. We hope that these proceedings will serve as a valuable reference for researchers and developers in the field of software architectures and mobility from institutions around the world.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.023 |
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".