SMT-Based Synthesis of Distributed Self-Stabilizing Systems
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Bibliographic record
Abstract
A self-stabilizing system is one that guarantees reaching a set of legitimate states from any arbitrary initial state. Designing distributed self-stabilizing protocols is often a complex task and developing their proof of correctness is known to be significantly more tedious. In this article, we propose an SMT-based method that automatically synthesizes a self-stabilizing protocol, given the network topology of distributed processes and description of the set of legitimate states. Our method can synthesize synchronous, asynchronous, symmetric, and asymmetric protocols for two types of stabilization, namely weak and strong . We also report on successful automated synthesis of a set of well-known distributed stabilizing protocols such as Dijkstra’s token ring, distributed maximal matching, graph coloring, and mutual exclusion in anonymous networks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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