Configuration Optimization with Limited ...
Type de document :
Communication dans un congrès avec actes
Titre :
Configuration Optimization with Limited Functional Impact
Auteur(s) :
Guégain, Edouard [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Taherkordi, Amir [Auteur]
University of Oslo [UiO]
Quinton, Clément [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Self-adaptation for distributed services and large software systems [SPIRALS]
Taherkordi, Amir [Auteur]
University of Oslo [UiO]
Quinton, Clément [Auteur]
Self-adaptation for distributed services and large software systems [SPIRALS]
Titre de la manifestation scientifique :
CAISE 2023 - 35th International Conference on Advanced Information Systems Engineering
Ville :
Zaragoza
Pays :
Espagne
Date de début de la manifestation scientifique :
2023-06-12
Titre de la revue :
Advanced Information Systems Engineering
Mot(s)-clé(s) en anglais :
Software
Variability
Optimization
Performance
Variability
Optimization
Performance
Discipline(s) HAL :
Informatique [cs]/Génie logiciel [cs.SE]
Résumé en anglais : [en]
Dealing with a large configuration space is a complex task for developers, especially when configurations must comply with both functional constraints and non-functional goals. In this paper, we introduce an approach to ...
Lire la suite >Dealing with a large configuration space is a complex task for developers, especially when configurations must comply with both functional constraints and non-functional goals. In this paper, we introduce an approach to optimize any set of performance indicators for an existing configuration, while meeting functional requirements. The efficiency of this approach is assessed by exhaustively optimizing a configurable system, and by analyzing how the algorithm navigates through the configuration space. This approach proves especially efficient at optimizing configurations through a minimal number of changes, thus limiting the impact on their functional behavior.Lire moins >
Lire la suite >Dealing with a large configuration space is a complex task for developers, especially when configurations must comply with both functional constraints and non-functional goals. In this paper, we introduce an approach to optimize any set of performance indicators for an existing configuration, while meeting functional requirements. The efficiency of this approach is assessed by exhaustively optimizing a configurable system, and by analyzing how the algorithm navigates through the configuration space. This approach proves especially efficient at optimizing configurations through a minimal number of changes, thus limiting the impact on their functional behavior.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Projet ANR :
Collections :
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