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Record W2963236193 · doi:10.48550/arxiv.1401.0970

Actions and Events in Concurrent Systems Design

2014· article· en· W2963236193 on OpenAlexaff
Valentín Cassano, T. S. E. Maibaum

Bibliographic record

VenuearXiv (Cornell University) · 2014
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Software Engineering Methodologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPrinciple of compositionalityMorphismComponent (thermodynamics)Computer scienceContext (archaeology)Programming languageSet (abstract data type)Theoretical computer scienceCategorical variableComponent-based software engineeringSoftware systemArtificial intelligenceSoftwareMathematicsPure mathematics

Abstract

fetched live from OpenAlex

In this work, having in mind the construction of concurrent systems from components, we discuss the difference between actions and events. For this discussion, we propose an(other) architecture description language in which actions and events are made explicit in the description of a component and a system. Our work builds from the ideas set forth by the categorical approach to the construction of software based systems from components advocated by Goguen and Burstall, in the context of institutions, and by Fiadeiro and Maibaum, in the context of temporal logic. In this context, we formalize a notion of a component as an element of an indexed category and we elicit a notion of a morphism between components as morphisms of this category. Moreover, we elaborate on how this formalization captures, in a convenient manner, the underlying structure of a component and the basic interaction mechanisms for putting components together. Further, we advance some ideas on how certain matters related to the openness and the compositionality of a component/system may be described in terms of classes of morphisms, thus potentially supporting a compositional rely/guarantee reasoning.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.932
Threshold uncertainty score0.361

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 head0.190
GPT teacher head0.223
Teacher spread0.032 · 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 teacher head, 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

Citations0
Published2014
Admission routes1
Has abstractyes

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