Verification of parameterized concurrent programs by modular reasoning about data and control
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
In this paper, we consider the problem of verifying thread-state properties of multithreaded programs in which the number of active threads cannot be statically bounded. Our approach is based on decomposing the task into two modules, where one reasons about data and the other reasons about control. The data module computes thread-state invariants (e.g., linear constraints over global variables and local variables of one thread) using the thread interference information computed by the control module. The control module computes a representation of thread interference, as an incrementally constructed data flow graph, using the data invariants provided by the data module. These invariants are used to rule out patterns of thread interference that can not occur in a real program execution. The two modules are incorporated into a feedback loop, so that the abstractions of data and interference are iteratively coarsened as the algorithm progresses (that is, they become weaker) until a fixed point is reached. Our approach is sound and terminating, and applicable to programs with infinite state (e.g., unbounded integers) and unboundedly many threads. The verification method presented in this paper has been implemented into a tool, called Duet. We demonstrate the effectiveness of our technique by verifying properties of a selection of Linux device drivers using Duet, and also compare Duet with previous work on verification of parameterized Boolean program using the Boolean abstractions of these drivers.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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