Evaluation of reusable concern-oriented goal models
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
A new unit of encapsulation called the concern is at the center of Concern-Orientation. Building on techniques for advanced Separation of Concerns, from Model-Driven Engineering, and from Software Product Lines, Concern-Orientation is a reuse paradigm that stipulates the use of three interfaces to enable broad, generic reuse: the variation, customization, and usage interfaces. Higher-level concerns reuse lower-level concerns, resulting in concern hierarchies where lower-level concern models are composed with higher-level concern models. As part of the variation interface, goal models are used to describe the impact of features of a concern on system qualities. Consequently, goal models of lower-level concerns must be combined with goal models of higher-level concerns to enable reasoning about system qualities in concern hierarchies. However, existing propagation-based reasoning mechanisms for goal models still assume a monolithic goal model, which is not appropriate for concern-oriented reuse. To address this issue, this paper presents novel modeling constructs to enable the reuse of lower-level goal models in the context of Concern-Orientation, extends existing propagation-based reasoning mechanisms of goal models for use in concern hierarchies, and reports on a proof-of-concept implementation of the novel modeling constructs and the extended reasoning mechanism.
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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 | 0.003 | 0.002 |
| 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 | 0.000 | 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