A taxonomy of software architecture-based reliability efforts
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Bibliographic record
Abstract
Due to the complexity of the current software systems and the diversity of their architectural styles and component models, architecture-based reliability is becoming a more important quality requirement than ever before. Architecture-based reliability efforts depend on the behavior of individual components and their interactions with respect to their influences on the system reliability. Depending on different viewpoints and assumptions, a component takes various definitions and forms. As a result, numerous reliability works that involve varieties of the underlying strategies, objectives, and parameters are proposed for software architectures. Classifying these efforts is important for creating and selecting potential solutions that handle the reliability of software applications. In this paper, we provide a taxonomy of architecture-based reliability efforts. We classify these efforts according to the reliability goals, component abstraction, and level of granularity. We explain the existing techniques considering their assumptions with respect to these classification parameters and provide detailed description about the specific issues and considerations of each class.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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