Goal-Oriented Requirements and Feature Modeling for Software Product Line Engineering
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
Models encapsulate functionalities and quality properties of a product family. Leveraging feature models for managing va- riability and commonalities of large-scale product families raises an important question: on what basis should the features of a product line be selected for a target software application, which is going to be derived from the product family. Thus, the selection of the most suitable features for a specific application requires the understanding of its stakeholders' intentions and also the relation- ship between their intentions and the available software features. To address this important issue, we adopt a standard goal-oriented requirements engineering framework, i.e., the i* framework, for identifying stakeholders' intentions and propose an approach to explicitly mapping and bridging features of a product line to stakeholders' goals and objectives. Herewith, we propose a novel approach to automatically pre-configuring a given feature model based on the objectives of the target product stakeholders. Also, our approach is able to elucidate the rationale behind the selection of the most important features of a family for a target application.
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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 | 0.000 | 0.003 |
| 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