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Over 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 selfmanaging systems further and to leverage the benefits of selfadaptation, 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.

Computational thinking (CT) uses concepts that are essential to computing and information science to solve problems, design and evaluate complex systems, and understand human reasoning and behavior. This way of thinking has important implications in computer sciences as well as in almost every other field. Therefore, we contend that CT should be taught in elementary schools and included in every university's educational curriculum. Several studies that measure the impact of teaching programming, analytical thinking, and CT have been conducted. In this review, we analyze and discuss findings from these studies and highlight the importance of learning programming with a focus on the development of CT skills at a young age. We also describe the tools that are available to improve the teaching of CT and provide a state-of-the-art overview of how programming is being taught at schools and universities in Colombia and around the world.

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Despite the valuable contributions on self-adaptation, most implemented approaches assume adaptation goals and monitoring infrastructures as non-mutable, thus constraining their applicability to systems whose context awareness is restricted to static monitors. Therefore, separation of concerns, dynamic monitoring, and runtime requirements variability are critical for satisfying system goals under highly changing environments. In this chapter we present DYNAMICO, a reference model for engineering adaptive software that helps guaranteeing the coherence of (i) adaptation mechanisms with respect to changes in adaptation goals; and (ii) monitoring mechanisms with respect to changes in both adaptation goals and adaptation mechanisms. DYNAMICO improves the engineering of self-adaptive systems by addressing (i) the management of adaptation properties and goals as control objectives; (ii) the separation of concerns among feedback loops required to address control objectives over time; and (iii) the management of dynamic context as an independent control function to preserve context-awareness in the adaptation mechanism.