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Umple

2020· book-chapter· en· W3080939604 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

VenueAdvances in systems analysis, software engineering, and high performance computing book series · 2020
Typebook-chapter
Languageen
FieldComputer Science
TopicModel-Driven Software Engineering Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAgile software developmentComputer scienceCodebaseUSableSoftware engineeringModeling languageCode generationCode (set theory)World Wide WebProgramming languageSource codeSoftwareSet (abstract data type)Operating system

Abstract

fetched live from OpenAlex

Umple is a technology designed to provide the benefits of model-driven engineering in a usable way. It is a textual modeling language, allowing agile developers to quickly incorporate state machines, associations, and many other modeling features into their codebase, with comprehensive code generation for multiple target languages. This significantly reduces the amount of code developers have to write. At the same time, Umple's always-on diagram generation and analysis allows quick understanding of model-driven projects and discovery of their defects. The chapter demonstrates the benefits of textual modeling languages and discusses multiple ways that Umple can help bring modeling to the agile development community, including its support for product-line engineering. Umple is in use worldwide, with the online version hosting over 200,000 user sessions a year.

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 categoriesMeta-epidemiology (narrow)
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 score0.640
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.001
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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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