Master data

Title: The Handbook of Engineering Self-Aware and Self-Expressive Systems
Subtitle:
Abstract:

When faced with the task of designing and implementing a new self-aware and self-expressive computing system, researchers and practitioners need a set of guidelines on how to use the concepts and foundations developed in the Engineering Proprioception in Computing Systems (EPiCS) project. This report provides such guidelines on how to design self-aware and self-expressive computing systems in a principled way. We have documented different categories of self-awareness and self-expression level using architectural patterns. We have also documented common architectural primitives, their possible candidate techniques and attributes for architecting self-aware and self-expressive systems. Drawing on the knowledge obtained from the previous investigations, we proposed a pattern driven methodology for engineering self-aware and self-expressive systems to assist in utilising the patterns and primitives during design. The methodology contains detailed guidance to make decisions with respect to the possible design alternatives, providing a systematic way to build self-aware and self-expressive systems. Then, we qualitatively and quantitatively evaluated the methodology using two case studies. The results reveal that our pattern driven methodology covers the main aspects of engineering self-aware and self-expressive systems, and that the resulted systems perform significantly better than the non-self-aware systems.

Keywords:
Publication type: Other publication (Authorship)
Publication date: 13.09.2014 (Online)
Published by: Computer Research Repository (CoRR)
Computer Research Repository (CoRR)
to publication
 ( )
Title of the series: -
Volume number: -
Issue: -
First publication: Yes
Version: -
Page: -
Total number of pages: 81 pp.

Versionen

Keine Version vorhanden
Publication date: 13.09.2014
ISBN (e-book): -
eISSN: -
DOI: -
Homepage: http://arxiv.org/abs/1409.1793
Open access
  • Stored in a repository

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Vernetzte und Eingebettete Systeme
Universitätsstraße 65-67
9020 Klagenfurt am Wörthersee
Austria
  -993640
   kornelia.lienbacher@aau.at
https://nes.aau.at/
To organisation
Universitätsstraße 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
  • 2020 - Electrical Engineering, Electronics, Information Engineering
Research Cluster No research Research Cluster selected
Citation index No citation index selected
Information about the citation index: Master Journal List
Peer reviewed
  • No
Publication focus
  • Science to Science (Quality indicator: III)
Classification raster of the assigned organisational units:
working groups No working group selected

Cooperations

No partner organisations selected

Articles of the publication

No related publications