Method
Scalabrino
The comprehensive model of Scalabrino et al. combines structural, textual, and visual features. We call the authors' released Java archive and pretrained classifier through a local adapter, wrapping method snippets in a minimal class where required. The published features and scoring logic are unchanged. Unsupported or failed samples are omitted.
Score scale: 0–1; higher is more readable.
Dataset results
| Dataset | Coverage | Spearman ρ |
|---|---|---|
| MBJP | 17/17 | 0.332 |
| Buse | 67/100 | 0.69 |
| Scalabrino | 200/200 | 0.602 |
| Dorn | 259/360 | 0.586 |
| Schnappinger | 293/304 | 0.407 |
| JetBrains | 119/119 | 0.342 |
| Java transformations | 1358/1400 | — |
| Python transformations | 0/1400 | — |