Multi-dispatch in the <i>Java Virtual Machine</i> (poster session)
Bibliographic record
Abstract
Mainstream object-oriented languages, such as C++ and Java, provide only a restricted form of polymorphic methods, namely single-receiver dispatch. In common programming situations, programmers must work-around this limitation. We detail how to extend the Java Virtual Machine to support multiple-dispatch and examine the complications that Java imposes on multiple-dispatch in practice. Our technique avoids changes to the Java programming language itself, maintains source-code and library compatibility, and isolates the performance penalty and semantic changes of multiple-dispatch to the program sections which use it. We have micro-benchmark and application-level performance results for a dynamic Most Specific Applicable (MSA) dispatcher, two table-based dispatchers (Multiple Row Displacement (MRD) and Single Receiver Projections (SRP)), and a tuned SRP dispatcher. Our general-purpose technique provides smaller dispatch latency than equivalent programmer-written double-dispatch code.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".