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Authors: Claudia Raibulet ; Francesca Fontana and Simone Carettoni

Affiliation: DISCo-Dipartimento di Informatica, Sistemistica e Comunicazione, Universita’ Degli Studi di Milano - Bicocca, Viale Sarca, 336, Edificio 14, Milan, Italy

ISBN: 978-989-758-421-3

Keyword(s): Self-Adaptive Systems, Non-Self-Adaptive Systems, Software Quality, Architectural Smells, Code Smells, Design Patterns.

Abstract: Self-Adaptive Systems are usually built of a managed part, implementing their functionality, and a managing part, implementing their self-adaptation. The complexity of self-adaptive systems results also from the existence of the managing part and the interaction between the managed and the managing parts. The non-self-adaptive systems may be seen as the managed part of self-adaptive systems. The self-adaptive systems are evaluated based on their performances resulted from the self-adaptation. However, self-adaptive systems are software systems, hence, also their software quality is equally important. Our analysis compares the internal quality of self-adaptive and non-self-adaptive systems by considering code smells, architectural smells, and GoF’s design patterns. This comparison provides an insight to the health of the self-adaptive systems with respect to the non-self-adaptive systems (the last being considered as a quality reference).

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Paper citation in several formats:
Raibulet, C.; Fontana, F. and Carettoni, S. (2020). SAS vs. NSAS: Analysis and Comparison of Self-Adaptive Systems and Non-Self-Adaptive Systems based on Smells and Patterns.In Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-421-3, pages 490-497. DOI: 10.5220/0009513504900497

@conference{enase20,
author={Claudia Raibulet. and Francesca Arcelli Fontana. and Simone Carettoni.},
title={SAS vs. NSAS: Analysis and Comparison of Self-Adaptive Systems and Non-Self-Adaptive Systems based on Smells and Patterns},
booktitle={Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2020},
pages={490-497},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009513504900497},
isbn={978-989-758-421-3},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - SAS vs. NSAS: Analysis and Comparison of Self-Adaptive Systems and Non-Self-Adaptive Systems based on Smells and Patterns
SN - 978-989-758-421-3
AU - Raibulet, C.
AU - Fontana, F.
AU - Carettoni, S.
PY - 2020
SP - 490
EP - 497
DO - 10.5220/0009513504900497

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