WSDarwin: automatic web service client adaptation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The service-oriented architecture paradigm prescribes the development of systems through the composition of services, i.e., network-accessible components, specified by (and invoked through) their WSDL interface descriptions. Systems thus developed need to be aware of changes in, and evolve with, their constituent services. To support this coevolution process, we have developed WSDarwin, a toolkit that facilitates both providers and clients in the evolution of service-oriented systems. In this work, we focus primarily on the comparison of service-interface versions, in order to precisely recognize their differences, and the adaptation of client applications. We propose a lightweight model to represent service interfaces, an efficient and accurate comparison method whose output can be seamlessly consumed by the adaptation process, a classification of changes in service interfaces based on their impact on client applications and, finally, a generic adaptation algorithm that can be applied for any type of change and on any client regardless of the implementation technology. We demonstrate this part of the WSDarwin toolkit on a client application invoking several versions from the Amazon EC2 web service and we report on the challenges we faced.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it