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Record W2129458963 · doi:10.1109/apsec.2000.896738

A study on static analysis in network of synchronizing FSMs

2002· article· en· W2129458963 on OpenAlexafffund
J. Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSynchronizingComputer scienceCorrectnessThread (computing)Finite-state machineSemaphoreNondeterministic algorithmJavaProgramming languageSynchronization (alternating current)Theoretical computer scienceAbstract state machinesDistributed computing

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.077
GPT teacher head0.321
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2002
Admission routes2
Has abstractyes

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