Bibliographic record
Abstract
We propose a formalization of the COSMIC Full Function Point (COSMIC-FFP) measure for the Real-time Object Oriented Modeling (ROOM) language. COSMIC-FFP is a measure of the functional size of software. It has been proposed by the COSMIC group as an adaptation of the function point measure for real-time systems. The definition of COSMIC-FFP is general and can be applied to any specification language. The benefits of our formalization are twofold. First it eliminates measurement variance, because the COSMIC informal definition is subject to interpretation by COSMIC-FFP raters, which may lead to different counts for the same specification, depending on the interpretation made by each rater. Second it allows the automation of COSMIC-FFP measurement for ROOM specifications, which reduces measurement costs. Finally, the formal definition of COSMIC-FFP can provide a clear and unambiguous characterization of COSMIC-FFP concepts which is helpful for measuring COSMIC-FFP for other object-oriented notations like UML.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".