Unique renaming of Java using source transformation
Bibliographic record
Abstract
We present a method for unique renaming declarations and references in Java programs using source transformation to XML markup. Each entity declaration and reference in the Java program is assigned a globally unique identifier (UID) based on its declaration scope and file. The UID serves as a key by which the entity's original declaration and all references can be found, and more importantly, by which information about the entity can be stored or retrieved from the design database. The resulting uniquely renamed source code makes it convenient and efficient to do further business logic and technical analysis that crosses the boundary between source code and the design database. UIDs are attached to entity references in the source code using XML markup, so that both the UID and the original source text of the declaration or reference are available in the renamed source program. While it is possible to generate unique names in an ad hoc manner, we show how to generate them using a combination of source transformations and design database inferences. This ensures that the notion of UID is consistent and well defined.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".