To deal with the increasing complexity of software systems and uncertainty of their environments, software engineers have turned to self-adaptivity. Self-adaptive systems are capable of dealing with a continuously changing environment and emerging requirements that may be unknown at design-time. However, building such systems cost-effectively and in a predictable manner is a major engineering challenge. In this paper, we explore the state-of-the-art in engineering self-adaptive systems and identify potential improvements in the design process. Our most important finding is that in designing self-adaptive systems, the feedback loops that control self-adaptation must become first-class entities. We explore feedback loops from the perspective of control engineering and within existing self-adaptive systems in nature and biology. Finally, we identify the critical challenges our community must address to enable systematic and well-organized engineering of self-adaptive and self-managing software systems.
%0 Book Section
%1 citeulike:6540636
%A Brun, Yuriy
%A Serugendo, Giovanna M.
%A Gacek, Cristina
%A Giese, Holger
%A Kienle, Holger
%A Litoiu, Marin
%A Müller, Hausi
%A Pezzè, Mauro
%A Shaw, Mary
%B Software Engineering for Self-Adaptive Systems
%C Berlin, Heidelberg
%D 2009
%E Cheng, Betty H.
%E Lemos, Rogério
%E Giese, Holger
%E Inverardi, Paola
%E Magee, Jeff
%I Springer-Verlag
%K self-adaptive
%P 48--70
%R 10.1007/978-3-642-02161-9_3
%T Software Engineering for Self-Adaptive Systems
%U http://dx.doi.org/10.1007/978-3-642-02161-9_3
%V 5525
%X To deal with the increasing complexity of software systems and uncertainty of their environments, software engineers have turned to self-adaptivity. Self-adaptive systems are capable of dealing with a continuously changing environment and emerging requirements that may be unknown at design-time. However, building such systems cost-effectively and in a predictable manner is a major engineering challenge. In this paper, we explore the state-of-the-art in engineering self-adaptive systems and identify potential improvements in the design process. Our most important finding is that in designing self-adaptive systems, the feedback loops that control self-adaptation must become first-class entities. We explore feedback loops from the perspective of control engineering and within existing self-adaptive systems in nature and biology. Finally, we identify the critical challenges our community must address to enable systematic and well-organized engineering of self-adaptive and self-managing software systems.
%& Engineering Self-Adaptive Systems Through Feedback Loops
%@ 978-3-642-02160-2
@incollection{citeulike:6540636,
abstract = {{To deal with the increasing complexity of software systems and uncertainty of their environments, software engineers have turned to self-adaptivity. Self-adaptive systems are capable of dealing with a continuously changing environment and emerging requirements that may be unknown at design-time. However, building such systems cost-effectively and in a predictable manner is a major engineering challenge. In this paper, we explore the state-of-the-art in engineering self-adaptive systems and identify potential improvements in the design process. Our most important finding is that in designing self-adaptive systems, the feedback loops that control self-adaptation must become first-class entities. We explore feedback loops from the perspective of control engineering and within existing self-adaptive systems in nature and biology. Finally, we identify the critical challenges our community must address to enable systematic and well-organized engineering of self-adaptive and self-managing software systems.}},
added-at = {2018-03-19T12:24:51.000+0100},
address = {Berlin, Heidelberg},
author = {Brun, Yuriy and Serugendo, Giovanna M. and Gacek, Cristina and Giese, Holger and Kienle, Holger and Litoiu, Marin and M\"{u}ller, Hausi and Pezz\`{e}, Mauro and Shaw, Mary},
biburl = {https://www.bibsonomy.org/bibtex/2f7bcf0492df832ed699fa5d855ba8b69/aho},
booktitle = {Software Engineering for Self-Adaptive Systems},
chapter = {Engineering Self-Adaptive Systems Through Feedback Loops},
citeulike-article-id = {6540636},
citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1573860},
citeulike-linkout-1 = {http://dx.doi.org/10.1007/978-3-642-02161-9_3},
citeulike-linkout-2 = {http://www.springerlink.com/content/32nm834361u37368},
citeulike-linkout-3 = {http://link.springer.com/chapter/10.1007/978-3-642-02161-9_3},
doi = {10.1007/978-3-642-02161-9_3},
editor = {Cheng, Betty H. and Lemos, Rog{\'{e}}rio and Giese, Holger and Inverardi, Paola and Magee, Jeff},
interhash = {91a546b18161d4dd640c8e6e4f8b4ea3},
intrahash = {f7bcf0492df832ed699fa5d855ba8b69},
isbn = {978-3-642-02160-2},
keywords = {self-adaptive},
pages = {48--70},
posted-at = {2011-04-25 15:49:30},
priority = {2},
publisher = {Springer-Verlag},
series = {Lecture Notes in Computer Science},
timestamp = {2018-03-19T12:24:51.000+0100},
title = {{Software Engineering for Self-Adaptive Systems}},
url = {http://dx.doi.org/10.1007/978-3-642-02161-9_3},
volume = 5525,
year = 2009
}