Consented consumer-centric non-functional property description and composition for SOA-based applications
Bibliographic record
Abstract
Non-functional properties (NFPs) play an important role in the service-oriented architecture (SOA). Consumer-centric NFPs are the NFPs that should be included in a service description to help service consumers decide whether a given service suits their needs. They can hence be used to enable NFP-based service selection and composition. However, nowadays, NFPs are often simply not advertised or are described in ad-hoc proprietary ways. Three important factors impede on the proper handling of NFPs in service descriptions: 1) the neglect of consumer perspectives in SOA; 2) the lack of adequate descriptive mechanisms for a number of NFPs; 3) a good understanding of NFP composability. This paper contributes a concrete syntax for an externally consented catalogue of 17 consumer-centric NFPs, together with composition algorithms that can be effectively used for defining, selecting, and composing services for NFP-aware SOA-based application designs. A realistic use case is used to illustrate the NFP composition algorithms. The NFP catalogue is also validated through its proof-of-concept integration with a mainstream technology: Web Service Description Language (WSDL).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".