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Ítem Improving context-awareness in self-adaptation using the DYNAMICO reference model(IEEE, 2013-05-20) Muller, Hausi A.Self-adaptation mechanisms modify target systems dynamically to address adaptation goals, which may evolve continuously due to changes in system requirements. These changes affect values and thresholds of observed context variables and monitoring logic, or imply the addition and/or deletion of context variables, thus compromising self-adaptivity effectiveness under static monitoring infrastructures. Nevertheless, self-adaptation approaches often focus on adapting target systems only rather than monitoring infrastructures. Previously, we proposed DYNAMICO, a reference model for self-adaptive systems where adaptation goals and monitoring requirements change dynamically. This paper presents an implementation of DYNAMICO comprising our SMARTERCONTEXT monitoring infrastructure and QoS-CARE adaptation framework in a self-adaptation solution that maintains its context-awareness relevance. To evaluate our reference model we use self-adaptive system properties and the Znn.com exemplar to compare the Rainbow system with our DYNAMICO implementation. The results of the evaluation demonstrate the applicability, feasibility, and effectiveness of DYNAMICO, especially for self-adaptive systems with context-awareness requirements. © 2013 IEEE.Ítem A framework for the generation and management of self-adaptive enterprise applications(IEEE, 2015-09-21) Tamura Morimitsu, GabrielDemand for self-adaptive enterprise applications has been on the rise over the last years. Such applications are expected to satisfy context-dependent quality requirements in varying execution conditions. Their dynamic nature constitutes challenges with respect to their architectural design and development, and the guarantee of the agreed quality scenarios at runtime. In this paper we present the constituting elements of Shift, a framework that integrates (i) facilities and mechanisms for managing self-adaptive enterprise applications, (ii) automated derivation of self-adaptive enterprise applications and their respective monitoring infrastructure, and (iii) decision support for the assisted recomposition of self-adaptive applications.
Ítem A framework for evaluating quality-driven self-adaptive software systems(ACM Press, 2011-05-23) Casallas, RubbyOver the past decade the dynamic capabilities of self-adaptive software-intensive systems have proliferated and improved significantly. To advance the field of self-adaptive and self-managing systems further and to leverage the benefits of self-adaptation, we need to develop methods and tools to assess and possibly certify adaptation properties of self-adaptive systems, not only at design time but also, and especially, at run-time. In this paper we propose a framework for evaluating quality-driven self-adaptive software systems. Our framework is based on a survey of self-adaptive system papers and a set of adaptation properties derived from control theory properties. We also establish a mapping between these properties and software quality attributes. Thus, corresponding software quality metrics can then be used to assess adaptation properties. © 2011 ACM.Ítem Self-adaptive applications: on the development of personalized web-tasking systems(ACM Press; Association for Computing Machinery, 2014-06-02) Müller, Hausi A.Personalized Web-Tasking (PWT) proposes the automation of user-centric and repetitive web interactions to assist users in the fulfilment of personal goals using internet systems. In PWT, both personal goals and internet systems are affected by unpredictable changes in user preferences, situations, system infrastructures and environments. Therefore, self-adaptation enhanced with dynamic context monitoring is required to guarantee the effectiveness of PWT systems that, despite context uncertainty, must guarantee the accomplishment of personal goals and deliver pleasant user experiences. This position paper describes our approach to the development of PWT systems, which relies on selfadaptation and its enabling technologies. In particular, it presents our runtime modelling approach that is comprised of our PWT Ontology and Goal-oriented Context-sensitive web-tasking (GCT) models, and the way we exploit previous SEAMS contributions developed in our research group, the DYNAMICO reference model and the SmarterContext Monitoring Infrastructure and Reasoning Engine. The main goal of this paper is to demonstrate how the most crucial challenges in the engineering of PWT systems can be addressed by implementing them as self-adaptive software.