Self-Adaptive System quality modeling

This paper investigates the effects of modeling dimensions in different State-of-the-art Frameworks, to mitigate the Impact of uncertainty in Self-Adaptive Systems. Self-Adaptive Software systems can modify their behavior according to environmental conditions without human interaction. Self-Adaptive property of a software system depends on a variety of aspects according to the system design and environmental conditions. These factors called modeling dimensions and system quality depends on these modeling dimensions. Software engineering for these systems deals with modifying behavior and uncertainty by using disciplines of software engineering; as a result different mapping techniques are recently introduced to tradeoff uncertainty in self-adaptive systems. This paper characterize these State-of-the-art mapping techniques according to set of challenges they are addressing and then compared these mapping techniques with modeling dimensions to find ignored factors and propose a systematic method to find out the best mapping technique to enhance the quality in Self-Adaptive Systems.