MétaCan
Menu
Back to cohort
Record W1812469182

Verifying protocols by model checking: a case study of the wireless application protocol and the model checker SPIN

2004· article· en· W1812469182 on OpenAlexaff
Yu-Tong He, Ryszard Janicki

Bibliographic record

VenueConference of the Centre for Advanced Studies on Collaborative Research · 2004
Typearticle
Languageen
FieldComputer Science
TopicFormal Methods in Verification
Canadian institutionsMcMaster University
Fundersnot available
KeywordsModel checkingComputer scienceProtocol (science)PromelaFormal verificationWirelessWireless Application ProtocolDatabase transactionFormal methodsDistributed computingProgramming languageWireless networkOperating system
DOInot available

Abstract

fetched live from OpenAlex

This paper deals with a formal verification of protocols, where the model checking approach is applied. As a case example, the Wireless Application Protocol (WAP Version 2.0) and the SPIN model checker are used. The paper concentrates on the Transaction Layer, in which some defects have been uncovered and proper corrections have been proposed.

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)0.012
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.203
GPT teacher head0.489
Teacher spread0.287 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueConference of the Centre for Advanced Studies on Collaborative ResearchSame topicFormal Methods in VerificationFrench-language works237,207