Toward a decidable notion of sequential consistency
Bibliographic record
Abstract
A memory model specifies a correctness requirement for a distributed shared memory protocol. Sequential consistency (SC) is the most widely researched model; previous work citealur1996 has shown that, in general, the SC verification problem is undecidable. We identify two aspects of the formulation found in citealur1996 that we consider to be highly unnatural; we call these non-prefix-closedness and prophetic inheritance. We conjecture that preclusion of such behavior yields a decidable version of SC, which we call decisive sequential consistency (DSC). We also introduce a structure called a phview window (VW), which retains information about a protocol's history, and we define the notion of a phVW-bound, which essentially bounds the size of the VWs needed to maintain DSC. We prove that the class of DSC protocols with VW-bound k is decidable; left conjectured is the hypothesis that all DSC protocols have such a bound, and further that the bound is computable from the protocol description. This hypothesis is true for all real protocols known to us; we verify its truth for the Lazy Caching protocol citeafek1993.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".