Detecting distributed software components that will not cause emergent behavior in asynchronous communication style
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
In distributed software systems (DSS) the functionality and/or control are distributed. This may cause the DSS components to show an unexpected behavior known as emergent behavior in the run time, which was not seen in their requirements and design. Emergent behaviors can have irreparable damages for companies. The savings in cost of detecting and fixing emergent behaviors in early phases is more than 20 times compared to fixing them after the deployment. The detecting methodologies usually utilize behavioral modeling which can face to state space explosion problem for large scale systems. Therefore, we approach this problem by detecting components that will not show emergent behavior and remove them from further analysis to help the scalability of these approaches. Previously, we have devised and implemented the algorithm for synchronous communications. In this paper, the extension of our method for detecting these components in the asynchronous communication style is presented which is closer to the real-world systems. The details of the technique and related algorithms are discussed.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 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