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Record W1550697281

Multi-dispatch in the Java virtual machine: design and implementation

2001· article· en· W1550697281 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsWestern UniversityUniversity of Alberta
Fundersnot available
KeywordsComputer scienceJavastrictfpProgramming languageReal time JavaOperating systemProgrammerJava concurrencyEconomic dispatchVirtual machineJava annotationJava Modeling LanguageObject-oriented programming
DOInot available

Abstract

fetched live from OpenAlex

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 applicationlevel performance results for a dynamic Most Specic Applicable (MSA) dispatcher, two table-based dispatchers (Mul- tiple Row Displacement (MRD) and Single Receiver Projections (SRP)), and a tuned SRP dispatcher. Our generalpurpose technique provides smaller dispatch latency than equivalent programmer-written double-dispatch code. 1...

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.927
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.313
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it