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Record W2130148612 · doi:10.1109/tools.2000.848753

UML for protocol engineering-extensions and experiences

2002· article· en· W2130148612 on OpenAlex

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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsTellabs (Canada)
FundersLappeenranta University of Technology
KeywordsComputer scienceApplications of UMLUnified Modeling LanguageProgramming languageClass diagramUML toolObject Constraint LanguageProtocol (science)Systems Modeling LanguageNotationImplementationModeling languageSoftware engineeringSoftware

Abstract

fetched live from OpenAlex

This paper presents a Unified Modeling Language profile for describing communications protocols. UML is a popular standardized, general-purpose visual language, but the current version lacks formal action semantics which is needed to define any complicated communications system. It is also difficult to generate an efficient protocol specific implementation from standard UML notation only. The authors developed a Graphical Protocol Description Language, a UML profile, to fulfil the needs of protocol engineering, UML stereotypes are used to add protocol-specific semantic information to class diagrams, enabling code generation for protocol implementations. GPDL contains graphical elements and a textual language that is used to describe actions in statechart transitions called the Generic Action Extension Language. A system described with GPDL can be converted to an implementation for any protocol framework. As an example a chain of tools which performs a translation from GPDL to SDL was developed by the authors.

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)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.862
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.244
Teacher spread0.221 · 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