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Record W1830619643

SableVM: a research framework for the efficient execution of java bytecode

2001· article· sv· W1830619643 on OpenAlexaff
Étienne Gagnon, Laurie Hendren

Bibliographic record

Venuenot available
Typearticle
Languagesv
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsBytecodeComputer scienceProgramming languageJavaJava bytecodeInterpreterInterface (matter)Garbage collectionVirtual machineJava annotationTable (database)Operating systemGenerics in JavaReal time JavaDatabaseGarbage
DOInot available

Abstract

fetched live from OpenAlex

SableVM is an open-source virtual machine for Java, intended as a r esearch framework for efficient execution of Java bytecode. The framework is essentially composed of an extensible bytecode interpreter using state-of-the-art and innovative techniques. Written in the C programming language, and assuming minimal system dependencies, the interpreter emphasizes high-level techniques to support efficient execution. In particular, we introduce new data layouts for classes, virtual tables and object instances that reduce the cost of interface method calls to that of normal virtual calls, allow ecient garbage collection and light synchronization, and make effective use of memory space.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0060.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.004

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 head0.098
GPT teacher head0.390
Teacher spread0.292 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations81
Published2001
Admission routes1
Has abstractyes

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