Bibliographic record
Abstract
The Unified Modeling Language (UML) is an industry standard for object-oriented software engineering. However, there is little empirical evidence on how the UML is used. This chapter reports results of a survey of UML practitioners. The authors found differences in several dimensions of UML diagram usage on software development projects, including frequency, the purposes for which they were used, and the roles of clients/users in their creation and approval. System developers are often ignoring the “Use Case-driven” prescription that permeates much of the UML literature, making limited or no use of either Use Case Diagrams or textual Use Case descriptions. Implications and areas requiring further investigation are discussed.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.042 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.001 | 0.054 |
| Open science | 0.012 | 0.019 |
| Research integrity | 0.001 | 0.017 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".