Response property checking via distributed state space exploration
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
A response property is a simple liveness property that, given state predicates p and q, asserts whenever a p-state is visited, a q-state will be visited in the future. This paper presents an efficient and scalable implementation for explicit-state model of checking response properties on systems with strongly- and weakly-fair actions, using a network of machines. Our approach is a novel twist on the One-Way-Catch-Them-Young (OWCTY) algorithm. Although OWCTY has a worst-case time complexity of O(n2m) where n is the number of states of the model, and m is the number of fair actions, we show that in practice, the run-time is a very small multiple of n. This allows our approach to handle large models with a large number of fairness constraints. Our implementation builds upon PREACH, a distributed, explicit-state model checking tool. We demonstrate the effectiveness of our approach by applying it to several standard benchmarks on some real-world, proprietary, architectural models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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