Bibliographic record
Abstract
In this paper, we present our study on statically analyzing design artifacts in multithreaded systems to check the correctness with respect to the nondeterministic behavior of the systems. The description of an abstract behavior of a multithreaded system on design stage can be naturally decomposed into the descriptions of the behavior of each thread and the description of the interactions among these threads. We assume that the behavior of each thread is described in terms of synchronizing finite state machine, a special finite state machine whose transitions may contain information about thread synchronization. Such information is expressed by way of some well-known synchronization mechanism from implementation languages. For the moment, we consider synchronization among multiple threads via shared objects, governed by Java monitors. The operational semantics for a network of such synchronizing finite state machines is provided in terms of labeled transition systems. The defined formal model is the basis for formally reasoning about the correctness of the design against certain properties that, due to the nondeterminism involved, may be hard to detect by testing final code.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".