On Failure Propagation in Component-Based Software Systems
Why this work is in the frame
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Bibliographic record
Abstract
Ensuring reliability in component-based software systems (CBSSs) is important for their effective applications in large scale and safety critical systems. However, only few techniques consider failure propagation in system architectures for system reliability assessment. Those techniques focus only on content failure propagation through component interfaces. Therefore, the evaluation of CBSS architectures based on the current techniques fails to consider the impacts of all failure types on system reliability. In this paper, we present a failure propagation analysis technique for CBSSs. We analyze failure propagation based on architectural service routes (ASRs). An ASR is a sequence of components that are connected through interfaces. We discuss the attributes of ASRs with respect to system components and present their impacts on failure propagation and consequently on the reliability of CBSSs. Further analysis determines upper and lower bounds of failure propagation among components and shows some relationships between system reliability and architectural attributes. Our technique is not limited to any failure type, and it considers failure scattering and masking. Therefore, unlike other works, the proposed technique demonstrates more accurate representation of the practical aspect of failure propagation in CBSSs. The technique can also be used to achieve reliable designs in the early design stages of CBSSs and to localize component faults in the operational stage. We compare different example architectures based on their impacts on system reliability.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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