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Record W2044438808 · doi:10.1145/1119655.1119683

AO challenge - implementing the ACID properties for transactional objects

2006· article· en· W2044438808 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
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsAspect-oriented programmingAtomicityComputer scienceSeparation of concernsConsistency (knowledge bases)Programming languageConcurrencySoftware engineeringConcurrency controlNotationSet (abstract data type)Isolation (microbiology)Object-oriented programmingDistributed computingSoftwareArtificial intelligenceDatabase transaction

Abstract

fetched live from OpenAlex

This paper presents a challenge case study to the aspect-oriented community: ensuring the ACID properties (atomicity, consistency, isolation and durability) for transactional objects. We define a set of ten base aspects, each one providing a well-defined reusable functionality. The base aspects are simple, yet have complex dependencies among each other. We then show how these base aspects can be configured and composed in different ways to implement different concurrency control and recovery strategies. This composition is delicate: some aspects conflict with each other, others have to be reconfigured dynamically at run-time. We believe that this case study can serve as a benchmark for aspect-oriented software development, in particular for evaluating the expressivity of aspect-oriented programming languages, the performance of aspect-oriented programming environments, and the suitability of aspect-oriented modeling notations.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.485
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.061
GPT teacher head0.280
Teacher spread0.218 · 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