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Record W90319414 · doi:10.5555/2557696.2557720

Explicit modelling of statechart simulation environments

2013· article· en· W90319414 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
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsDebuggingComputer scienceFormalism (music)VisualizationProgramming languageModel transformationArchitectureModel checkingSoftware engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, we propose an experimentation environment for the interactive simulation of Statechart models. We choose the Statecharts formalism as the most appropriate formalism to model and synthesize the environment. We take inspiration from software debugging as well as from simulation experimentation to explicitly model the detailed reactive behaviour of our environment. We map program debugging techniques such as execution modes, steps, and breakpoints to the simulation domain. We further explore how to integrate the notion of simulation time for the purpose of (scaled) real-time visualisation. Finally, we provide support for a (browser)clientserver architecture, again making use of the features of Statecharts. We build the experimentation model on top of the model to be simulated by instrumenting it using model transformation techniques. The entire Statechart modelling, simulation, and experimentation environment described in this work is supported by our tool, AToMPM. 1.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.441
Threshold uncertainty score0.204

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 head0.084
GPT teacher head0.273
Teacher spread0.189 · 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