Migrating legacy data structures based on variable overlay to Java
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Legacy information systems, such as banking systems, are usually organized around their data model. Hence, when these systems are migrated to modern environments, translation of the data model involves the most critical decisions, having strong implications on the rest of the translation. In this paper, we report our experience and describe the approaches adopted in migrating a large banking system (ten million lines of code) to Java, starting from a proprietary data model which gives programmers explicit control of the variable overlay in memory. After presenting the basic translation scheme, we discuss the exceptions that may occur in practice. Then, we consider two heuristic approaches useful to reduce the number of cases where a behavior equivalent to that of unions must be reproduced in Java. Finally, we comment on the experimental results obtained so far. Copyright © 2009 John Wiley & Sons, Ltd.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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