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Record W2015269143 · doi:10.1145/1133373.1133389

Brittle systems will break - not bend

2002· article· en· W2015269143 on OpenAlexaff
Yvonne Coady, Gregor Kiczales, Joon Ong, Andrew Warfield, Michael J. Feeley

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSecurity and Verification in Computing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer scienceModular designDaemonAspect-oriented programmingImplementationProgramming languageContext (archaeology)Kernel (algebra)AllocatorCode (set theory)Operating systemSoftware

Abstract

fetched live from OpenAlex

As OS code moves to new settings, it must be continually reshaped. Kernel code however, is notoriously brittle -- a small, seemingly localized change can break disparate parts of the system simultaneously. The problem is that the implementation of some system concerns are not modular because they naturally crosscut the system structure.Aspect-oriented programming proposes new mechanisms to enable the modular implementation of cross-cutting concerns. This paper evaluates aspect-oriented programming in the context of two crosscutting concerns in a FreeBSD 4.4 kernel -- page daemon activation and disk quotas. The ways in which aspects allowed us to make these implementations modular, the impact they have on comprehensibility and configurability, and the costs associated with supporting a prototype of an aspect-oriented runtime environment are presented.

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)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.008
Scholarly communication0.0060.014
Open science0.0010.006
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0210.010

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 head0.041
GPT teacher head0.226
Teacher spread0.186 · 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 designTheoretical or conceptual
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

Citations7
Published2002
Admission routes1
Has abstractyes

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