Claims and evidence for architecture-based self-adaptation: A systematic literature review

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Abstract

Engineering the upcoming generation of software systems and guaranteeing the required qualities is complex due to the inherent uncertainties at design time, such as new user needs and changing availability of resources. Architecture-based self-adaptation is a promising approach to tackle these challenges. In this approach, a system maintains a model of itself and adapts itself to realize particular quality objectives using a feedback loop. Despite a vast body of work, no systematic study has been performed on the claims associated with architecture-based self-adaptation and the evidence that exists for these claims. As such insight is important for researchers and engineers, we performed a systematic literature review covering 20 leading software engineering conferences and journals in the field, resulting in 121 studies used for data collection. The review shows that self-adaptation is primarily used to improve performance, reliability, and flexibility. The tradeoffs implied by self-adaptation have not received much attention, and evidence is mainly obtained from simple examples. From the study, we derive a number of recommendations for future research in architecture-based self-adaptive systems. © 2013 Springer-Verlag.

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Weyns, D., & Ahmad, T. (2013). Claims and evidence for architecture-based self-adaptation: A systematic literature review. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7957 LNCS, pp. 249–265). https://doi.org/10.1007/978-3-642-39031-9_22

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