Enhanced Configuration Generation Approach for Highly Available COTS Based Systems
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 design of configurations for high availability management is a complex and error prone task. Automation of the process is a first step towards improving the quality of such configurations and for exploring the different potential solutions for a given set of requirements. An automated approach for configuration generation for applications deployed on top of the Service Availability Forum (SAForum) middleware has been proposed in the literature. This approach, however, may generate several configurations among which some may not meet the required level of service availability. Therefore, these configurations need to be analyzed to select one for the deployment. This is a complex process as many configurations may be generated and considered throughout the process. In this paper, we propose to enhance this configuration generation approach with a method to eliminate early in the generation process some configurations that cannot meet the service availability requirement. The method estimates the service availability for the different possible combinations of software components, which can provide the requested services, taking into account the properties of these components and the behaviour of the SAForum middleware.
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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 | 0.001 |
| 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 | 0.000 | 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 it