Proceedings of the 3rd ACM workshop on Software engineering for pervasive services
Bibliographic record
Abstract
Welcome to the ACM Workshop on Software Engineering for Pervasive Services 2008! First created during ICPS'06 to become the meeting place of formal methods and pervasive worlds, this workshop has actually received in its first 3 occurences a surprising amount of submissions related to software architectures. Probably this proves that the future of pervasive services is already here, and we are happy this year to give to our workshop a taste of real applied techniques. Johann Bourcier from Grenoble, France, who organizes the Demos part of ICPS'08, will give us his point of view and new challenges. For the first time a semi formal approach - based on UML - will be presented, by Dhaminda Abeywickrama and Sita Ramakrishnan from Monash University, Australia. We strongly hope that this will illustrate the bridge that the SEPS Workshop is likely to create between several communities. Also very stimulating, we received this year a non academic work, mostly motivated by the network aspects of pervasive services and addressing security problems. This work will be presented by Ruan He and Marc Lacoste from the Orange Labs. Among others, this work brings to SEPS an interesting though probably difficult opening on the future problems to be solved in the domain of monitoring of pervasive systems. Miss Kouadri-Mostefaoui from Oxford will show us the latest results about the practical testing of webservices. The Programming Technology Lab from Brussel is the companion of SEPS Workshop since the beginning, thanks to the AmbientTalk community; it is one more time the case this year, with a new concept, the so-called approach. It remarkably addresses the dynamical aspects of pervasive applications using a terminology which reminds mathematical topology like strech or retract. Let us dream together to a bridge from our workshop to algebraic topology! Resilient Actors is a common work of Jorge Vallejos and 5 co-authors.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".