Model oriented programming: bridging the code-model divide
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.
Bibliographic record
Abstract
Model Driven Engineering proposes the use of models as the main development artifacts. This methodology involves generating code from models and then perhaps adding some details to the generated code. Frequently, it is required to also reverse-engineer code to generate models. Despite the wide acceptance of modeling benefits, the use of Model Driven Engineering practices remains limited. We present model oriented programming as a new paradigm to reduce the ever-present tension between model-centric and code-centric development styles. The core of this approach is to add UML abstractions such as associations and state machines directly into a high-level programming language code. In this approach, model diagrams become just another abstract view of the code. The need for reverse engineering is eliminated, since everything in the diagram is represented directly in the code. Model orientation is illustrated using Umple, a working model oriented programming platform. A functional layer of an airline reservation system is presented as a case study.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it