A Tool for Formal Feature Modeling Based on BDDs and Product Families Algebra.
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Bibliographic record
Abstract
Feature models are commonly used to capture the commonality and the variability of product families. There are several feature model notations that correspondingly depict the concepts of feature modeling techniques. Therefore, the tools based on them reflect this diversity in the notations used and the fuzziness of the concepts adopted. We propose a tool based on Product Families Algebra (PFA) and on Binary Decision Diagrams (BDD). The first brings the mathematical formalism to the specifications of product families and the mathematical theory that enables calculations on featuremodels. The second brings efficient algorithms in time and in space. Hence, the tool allows several algebraic manipulations of feature models algebraically specified. The paper discusses the architecture of the tool, and the process through which a term in PFA is translated into a term formed by BDD symbols and operations. A case study is presented to illustrate the tool’s key functionalities.
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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 | 0.001 |
| 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