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Record W2027222319 · doi:10.1145/1286821.1286823

Encapsulating objects with confined types

2007· article· en· W2027222319 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueACM Transactions on Programming Languages and Systems · 2007
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsnot available
FundersMcGill UniversityPurdue UniversityDeutscher Akademischer AustauschdienstNational Science Foundation
KeywordsComputer scienceCode refactoringProgramming languageCompilerJavaObject-oriented programmingEncapsulation (networking)Source codeSoftwareSoftware engineering

Abstract

fetched live from OpenAlex

Object-oriented languages provide little support for encapsulating objects. Reference semantics allows objects to escape their defining scope, and the pervasive aliasing that ensues remains a major source of software defects. This paper presents Kacheck/J, a tool for inferring object encapsulation properties of large Java programs. Our goal is to develop practical tools to assist software engineers, thus we focus on simple and scalable techniques. Kacheck/J is able to infer confinement —the property that all instances of a given type are encapsulated in their defining package. This simple property can be used to identify accidental leaks of sensitive objects, as well as for compiler optimizations. We report on the analysis of a large body of code and discuss language support and refactoring for confinement.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.614

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 head0.018
GPT teacher head0.268
Teacher spread0.250 · 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