Action-Driven Consistency for Modular Multi-Language Systems with Perspectives
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 advocates the use of different modelling languages and multiple views to describe the characteristics of a complex system. This allows to express a specific system characteristic with the most appropriate modelling language. However, establishing the conceptual relationships between elements from different languages and then consistently maintaining the links between model elements are non-trivial tasks. In this paper, we propose Action-Driven Consistency (ADC) for maintaining the links between different model elements from different languages defined with the Perspectives for Multi-Language Systems (PML) framework. PML aims to promote modularity in language reuse, inter-language consistency, and combination of languages. A perspective groups different languages, each playing a role for a common modelling purpose. PML defines perspective actions based on existing language actions to maintain consistent models. In this work, we present generic templates from which perspective actions can be generated given relationships between language metaclasses. This allows the perspective designer to focus on these key relationships and frees her from the error-prone implementation of perspective actions. We illustrate our approach with a perspective that combines class diagram and use case diagram languages for the purpose of requirement elicitation and apply it to a bank application.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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