On the completeness of compositional reasoning methods
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
Hardware systems and reactive software systems can be described as the composition of several concurrently active processes. Automated reasoning based on model checking algorithms can substantially increase confidence in the overall reliability of a system. Direct methods for model checking a concurrent composition, however, usually suffer from the explosion in the number of program states that arises from concurrency. Reasoning compositionally about individual processes helps mitigate this problem. A number of rules have been proposed for compositional reasoning, typically based on an assume-guarantee reasoning paradigm. Reasoning with these rules can be delicate, as some are syntactically circular in nature, in that assumptions and guarantees are mutually dependent. This is known to be a source of unsoundness. In this article, we investigate rules for compositional reasoning from the viewpoint of completeness . We show that several rules are incomplete: that is, there are properties whose validity cannot be established using (only) these rules. We derive a new, circular, reasoning rule and show it to be sound and complete. We show that the auxiliary assertions needed for completeness need be defined only on the interface of the component processes. We also show that the two main paradigms of circular and noncircular reasoning are closely related, in that a proof of one type can be transformed in a straightforward manner to one of the other type. These results give some insight into the applicability of compositional reasoning methods.
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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) | 0.000 | 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