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Davide Devescovi

dblp:26/2227 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2007
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Software engineering, system software, and programming languages
1 paper
Requirements engineering and software design · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Requirements engineering and software design › software architecture
self-adaptive systems
0.112007
An infrastructure for autonomic system development: the selflet approach · ASE 2007
Distributed systems › self-adaptive systems
autonomic computing
0.112007
An infrastructure for autonomic system development: the selflet approach · ASE 2007
Distributed systems › self-adaptive systems › autonomic computing
self-managing systems
0.112007
An infrastructure for autonomic system development: the selflet approach · ASE 2007

Methods — techniques the papers use, named apart from their topics

policy-based self-management · 0.1
YearPublicationVenuePosition
2007 An infrastructure for autonomic system development: the selflet approach
abstract
Autonomic computing is an emergent field for the development of large-scale, self-managing, complex distributed computer-based systems. This paper aims to be a practical approach to Autonomic Computing, by defining and implementing a generic model for autonomic systems, allowing software developers to create autonomic applications using a common and comprehensive infrastructure. In particular, this paper defines a simple but complete model andarchitecture of an autonomic computing element called SelfLet, which could be the building components used to create autonomic systems. SelfLets can be defined by specifying their behaviour, the abilities and goals they need to use and/or provide, and a high-level policy guiding their self-management.
Davide Devescovi, Elisabetta Di Nitto, Raffaela Mirandola
ASE1