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Record W2158735796 · doi:10.1109/icsm.2006.35

Managing Concern Interfaces

2006· article· en· W2158735796 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

VenueProceedings/Proceedings - Conference on Software Maintenance · 2006
Typearticle
Languageen
FieldComputer Science
TopicSoftware Engineering Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsComputer scienceInterface (matter)User interfaceApplication programming interfaceRelation (database)Information hidingSeparation of concernsSoftwareSoftware engineeringHuman–computer interactionInterface description languageProgramming languageDatabaseArtificial intelligenceOperating system

Abstract

fetched live from OpenAlex

Programming languages provide various mechanisms to support information hiding. One problem with information hiding, however, is that providing a stable interface behind which to hide implementation details involves fixing in advance the services offered through the interface. We introduce a flexible approach to define and manage interfaces to achieve separation of concerns in evolving software. Our approach involves explicitly specifying interface and implementation classes for individual concerns, and automatically classifying implementation classes based on their relation to the interface. Our approach is supported by JMantlet, a tool that provides advanced interface management within an integrated development environment. We report on a case study of a large system that provides evidence that flexible interface management is desirable and adequately supported by our approach

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0040.001
Research integrity0.0000.001
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 head0.027
GPT teacher head0.259
Teacher spread0.232 · 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