Deadlock detection by fair reachability analysis: from cyclic to multi-cyclic protocols (and beyond?)
Bibliographic record
Abstract
We generalize the technique of fair reachability analysis to multi-cyclic protocols modeled as networks of communicating finite state machines, where a number of cyclic protocols are interconnected in such a way that any two component cyclic protocols share at most one process and each channel in the protocol belongs to exactly one component cyclic protocol. By composing the fair reachability relations of the component cyclic protocols, we prove that the set of fair reachable states of a multi-cyclic protocol is exactly the set of reachable states that are of equal channel length with respect to each of its component cyclic protocols. As a result, each deadlock state is fair reachable, and deadlock detection is decidable for the class of multi-cyclic protocols whose fair reachable state spaces are finite. Under the assumption that the underlying communication topology of a protocol is strongly connected, we show that fair reachability analysis is inherently infeasible for logical correctness validation beyond multi-cyclic protocols.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".