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Record W2040233837 · doi:10.5555/2682923.2682960

Reducing CTL-live Model Checking to First-Order Logic Validity Checking

2014· article· en· W2040233837 on OpenAlexaff
Amirhossein Vakili, Nancy A. Day

Bibliographic record

VenueFormal Methods in Computer-Aided Design · 2014
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsModel checkingComputation tree logicKripke structureCTL*Computer scienceTemporal logicModal μ-calculusAbstraction model checkingTheoretical computer sciencePartial order reductionLivenessLinear temporal logicAbstractionAlgorithmDescription logicMultimodal logicZeroth-order logic

Abstract

fetched live from OpenAlex

Temporal logic model checking of infinite state systems without the use of iteration or abstraction is usually considered beyond the realm of first-order logic (FOL) reasoners because of the need for a fixpoint computation. In this paper, we show that it is possible to reduce model checking of a finite or infinite Kripke structure that is expressed in FOL to a validity problem in FOL for a fragment of computational tree logic (CTL), which we call CTL-live. CTL-live includes the CTL connectives that are traditionally used to express liveness properties. Our reduction can form the basis for methods that use FOL reasoning techniques directly to accomplish model checking of CTL-live properties without the need for fixpoint operators, transitive closure, abstraction, or induction.

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)0.014
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.181
GPT teacher head0.392
Teacher spread0.212 · 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

Citations7
Published2014
Admission routes1
Has abstractyes

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