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  • 1.
    Ahmad, Tanvir
    et al.
    Linnaeus University, Faculty of Engineering and Technology, Department of Computer Science.
    Haider, Muhammad Ashfaq
    Linnaeus University, Faculty of Engineering and Technology, Department of Computer Science.
    A Systematic Literature Review on Claims and supporting Evidence for Self-Adaptive Systems2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 2.
    Weyns, Danny
    et al.
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Ahmad, Tanvir
    Linnaeus University, Faculty of Technology, Department of Computer Science.
    Claims and Evidence for Architecture-Based Self-Adaptation: A Systematic Literature Review2013In: Software Architecture: 7th European Conference, ECSA 2013, Montpellier, France, July 1-5, 2013. Proceedings, Springer, 2013, p. 249-265Conference paper (Refereed)
    Abstract [en]

    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 architecturebased self-adaptive systems.

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