Method
Dorn
We reconstruct the Dorn model from the public feature data and released visual-metric implementations. Metrics available for fewer than 80% of training samples are excluded; forward selection retains seven features, and logistic regression is fitted on all 360 Dorn samples. A thin adapter selects the appropriate language analyzer without changing metric formulas or wrapping Java snippets. The score is the readable-class probability.
Score scale: 0–1; higher is more readable.
Dataset results
| Dataset | Coverage | Spearman ρ |
|---|---|---|
| MBJP | 17/17 | 0.375 |
| Buse | 100/100 | 0.603 |
| Scalabrino | 200/200 | 0.39 |
| Dorn | 360/360 | 0.618 |
| Schnappinger | 304/304 | 0.565 |
| JetBrains | 119/119 | -0.053 |
| Java transformations | 1400/1400 | — |
| Python transformations | 1386/1400 | — |