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Record W2289912058 · doi:10.11575/prism/30491

A Survey Paper on Software Architecture Visualization

2008· article· en· W2289912058 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

VenueOpen MIND · 2008
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSoftware visualizationComputer scienceVisualizationSoftware engineeringSoftware architectureResource-oriented architectureSoftware architecture descriptionSoftwareArchitectureData scienceSoftware developmentReference architectureSoftware constructionArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

Understanding the software architecture is a vital step towards building and maintaining software systems. But software architecture is an intangible conceptual entity. Therefore, it is hard to comprehend a software architecture without a visual mapping that reduces the burden on the human brain. Visualizing software architecture has been one of the most important topics in software visualization. Not only are architects interested in this visualization but also developers, testers, project managers and even customers. This paper is a survey on recent and key literature on software architecture visualization. It touches on efforts that defined what characteristics an effective visualization should have. It compares various efforts in this discipline according to taxonomies such as dimensionality, multiplicity of views and use of metaphors. The paper also discusses trends and patterns in recent research and addresses research questions that are still open for further investigation.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.897

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.059
GPT teacher head0.326
Teacher spread0.267 · 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