Initializing Global Objects: Time and Order
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Object-oriented programming has been bothered by an awkward feature for a long time: static members . Static members not only compromise the conceptual integrity of object-oriented programming, but also give rise to subtle initialization errors, such as reading non-initialized fields and deadlocks. The Scala programming language eliminated static members from the language, replacing them with global objects that present a unified object-oriented programming model. However, the problem of global object initialization remains open, and programmers still suffer from initialization errors. We propose partial ordering and initialization-time irrelevance as two fundamental principles for initializing global objects. Based on these principles, we put forward an effective static analysis to ensure safe initialization of global objects, which eliminates initialization errors at compile time. The analysis also enables static scheduling of global object initialization to avoid runtime overhead. The analysis is modular at the granularity of objects and it avoids whole-program analysis. To make the analysis explainable and tunable, we introduce the concept of regions to make context-sensitivity understandable and customizable by programmers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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