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Record W2895553469 · doi:10.1145/3270112.3270115

Documenting Simulink designs of embedded systems

2018· article· en· W2895553469 on OpenAlexaff
Alexander Schaap, Gordon Marks, Vera Pantelic, Mark Lawford, Gehan Selim, Alan Wassyng, Lucian M. Patcas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDocumentationComputer scienceSoftware engineeringSoftwareSoftware designGenerator (circuit theory)Systems engineeringSoftware documentationSignature (topology)Software systemSoftware developmentEmbedded systemSoftware constructionProgramming languageEngineering

Abstract

fetched live from OpenAlex

The importance of appropriate software design documentation has been well-established. Yet in industrial practice design documentation of large software systems is often out of date or entirely lacking in large part due to the effort required to produce and maintain useful design documents. While model-based design (mbd) partially addresses this problem, large complex models still require additional design documentation to enable development and maintenance. This paper introduces tool support for documenting the Software Design Description (sdd) of embedded systems developed using mbd with Simulink. In particular, the paper proposes a template for a sdd of a Simulink model. Then, the tool support we have developed for semi-automatic generation of sdds from the template is introduced. The tool support integrates MathWorks' Simulink Report Generator and our previously developed Signature Tool that identifies the interfaces of Simulink subsystems.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.027
GPT teacher head0.273
Teacher spread0.246 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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