2 nd Workshop on Leveraging REST in Enterprise Service Systems
Bibliographic record
Abstract
During the last few years resource-orientation and RESTful Web service design has been gaining significant traction as an alternative paradigm for building service-oriented architectures. Resource-orientation emerged as a solution to various shortcomings that have been identified for WS* standards and protocols and especially due to the significant technical and protocol complexity they entail. On the other hand, REST was defined as an architectural style and its primary purpose was to support the design of content-centric network-based high-scale architectures such as the Web. These architectures differ significantly from the procedure-oriented conceptualizations that have traditionally characterized service-oriented enterprise systems. Consequently, designers of such systems that are considering resource-orientation and REST as their architecture of choice are facing several issues and challenges. These challenges relate to the design as well as the implementation of modern business systems that encompass complex functional and non-functional requirements. In this workshop, we examined a broad set of issues related to utilizing REST as the primary architectural style for building enterprise service systems and discussed opportunities, implications and challenges that arise in this context. More specifically, we considered state-of-the-art approaches that have been proposed with regards to: a) modeling, designing, implementing, and composing resource-oriented service systems, b) RESTful Web service design principles, practices and maturity models, c) frameworks and practices for migrating or adapting existing systems to provide resource-oriented and RESTful interfaces and d) compliance evaluation methodologies for REST-based interfaces.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".