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Record W4255962326 · doi:10.2991/ijndc.2016.4.1.7

Using SPIN to Check Simulink Stateflow Models

2016· article· en· W4255962326 on OpenAlex
Chikatoshi Yamada, D. Michael Miller

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venue˜The œInternational journal of networked and distributed computing · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBusiness Process Modeling and Analysis
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Education, Culture, Sports, Science and TechnologyCMC Microsystems
KeywordsStateflowComputer scienceProgramming languageEmbedded systemSoftware engineeringMATLAB

Abstract

fetched live from OpenAlex

Verification is critical to the design of large and complex systems.SPIN is a well-known and extensively used verification tool.In this paper, we consider two tool chains, one existing, WSAT, and one introduced here, that support using SPIN to model check systems specified as Simulink Stateflow models.We present algorithms for doing the necessary translations and present empirical results that show the chain using tools introduced in this paper performs better than the one using the existing WSAT tool.We also show that these tools allow SPIN to be used for model checking nondeterministic Stateflow models in addition to deterministic ones.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.706
Threshold uncertainty score0.411

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.275
Teacher spread0.234 · 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