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Enregistrement W2616935805

Proceedings of the 2006 international workshop on Self-adaptation and self-managing systems

2006· article· en· W2616935805 sur OpenAlex

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affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
aboutLe titre ou le résumé porte un signal canadien du lexique géographique.

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineComputer Science
ThématiqueAdvanced Software Engineering Methodologies
Établissements canadiensUniversity of Victoria
Organismes subventionnairesnon disponible
Mots-clésComputer scienceAdaptation (eye)Flexibility (engineering)Software engineeringAutonomic computingNotationSoftware systemFault toleranceSystem of systemsSoftwareDistributed computingSystems design
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

An increasingly important requirement for a software-based system is the ability to self-manage by adapting itself at run time to handle such things as changing user needs, system intrusions or faults, a changing operational environment, and resource variability. Such a system must configure and reconfigure itself, augment its functionality, continually optimize itself, protect itself, and recover itself, while keeping its complexity hidden from the user.The topic of self-adaptive and self-managing systems has been studied by various communities, including software architectures, fault-tolerant computing, robotics, control systems, programming languages, and biologically-inspired computing. The goal of this workshop is to bring together researchers and practitioners from many of these diverse areas to discuss the fundamental principles, state of the art, and critical challenges of self-adaptive systems. Specifically, we intend to focus on the software engineering aspects, including the methods, architectures, algorithms, techniques, and tools that can be used to support dynamic adaptive behavior.Self-adaptation in self-managing systems represents a major new concern for software engineering. While in the past methods, tools, and notations have focused on the problem of preventing defects from occurring in our fielded systems, increasingly this is not enough. In addition, systems must take a much more aggressive role in handling and adapting to run time problems. A central concern then becomes the engineering mechanisms that can support self-adaptation. Too often today's systems achieve run time flexibility only by hard wiring in special-purpose, low-level code (like exceptions and time outs) that is difficult to change, reuse, or analyze.The ICSE 2006 SEAMS workshop is a continuation of a number of successful workshops in the area of self-managing systems held at ICSE and FSE in recent years, including the FSE 2002 and 2004 Workshops on Self-Healing (Self-Managed) Systems (WOSS), ICSE 2005 Workshop on Design and Evolution of Autonomic Application Software (DEAS), and the ICSE 2002, 2003, 2004 and 2005 Workshops on Architecting Dependable Systems (WADS). The objective is to consolidate the interest in the software engineering community on autonomic, self-managing, self-healing, self-optimizing, self-configuring, and self-adaptive systems through this new integrated workshop. This will be the first of several workshops to assess progress and identify challenges in this important area.We have received 22 submissions from academic and industrial contributors. Each paper was reviewed by at least 3 members of the Program Committee, and a total of 13 full papers have been accepted for presentation. We are thankful for the support and dedication of the Program Committee members towards making this workshop a success. The Program Committee consisted of: Gordon Blair (University of Lancaster, UK), Cristina Gacek (University of Newcastle upon Tyne, UK) Mike Hinchey (NASA Goddard, USA), Marin Litoiu (IBM Toronto, Canada), Neno Medvidovic (University of Southern California, USA), John Mylopoulos (University of Toronto, Canada), Masoud Sadjadi (Florida International University, USA), Dennis Smith (SEI, USA), Roy Sterritt (University of Ulster, UK), Alexander Wolf (University of Lugano, Switzerland), Kenny Wong (University of Alberta, Canada).

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: Méthodes
Score de désaccord entre enseignants0,607
Score d'incertitude au seuil0,215

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,242
Écart entre enseignants0,223 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle