The carefully reviewed papers in this state-of-the-art survey describe a wide range of approaches coming from different strands of software engineering, and look forward to future challenges facing this ever-resurgent and exacting field of research.

- support an adaptive culture or mindset, in which change and uncertainty are assumed to be the natural state--not a false expectation of order- introduce frameworks to guide the iterative process of managing change- institute collaboration, the interaction of people on three levels: interpersonal, cultural, and structural- add rigor and discipline to the RAD approach, making it scalable to the uncertainty and complexity of real-life undertakings

A concise and practical introduction to the foundations and engineering principles of self-adaptation Though it has recently gained significant momentum, the topic of self-adaptation remains largely under-addressed in academic and technical literature. This book changes that. Using a systematic and holistic approach, An Introduction to Self-adaptive Systems: A Contemporary Software Engineering Perspective provides readers with an accessible set of basic principles, engineering foundations, and applications of self-adaptation in software-intensive systems. It places self-adaptation in the context of techniques like uncertainty management, feedback control, online reasoning, and machine learning while acknowledging the growing consensus in the software engineering community that self-adaptation will be a crucial enabling feature in tackling the challenges of new, emerging, and future systems. The author combines cutting-edge technical research with basic principles and real-world insights to create a practical and strategically effective guide to self-adaptation. He includes features such as: An analysis of the foundational engineering principles and applications of self-adaptation in different domains, including the Internet-of-Things, cloud computing, and cyber-physical systems End-of-chapter exercises at four different levels of complexity and difficulty An accompanying author-hosted website with slides, selected exercises and solutions, models, and code Perfect for researchers, students, teachers, industry leaders, and practitioners in fields that directly or peripherally involve software engineering, as well as those in academia involved in a class on self-adaptivity, this book belongs on the shelves of anyone with an interest in the future of software and its engineering.

This book discusses the problems and challenges in the interdisciplinary research field of self-adaptive software systems. Modern society is increasingly filled with software-intensive systems, which are required to operate in more and more dynamic and uncertain environments. These systems must monitor and control their environment while adapting to meet the requirements at runtime. This book provides promising approaches and research methods in software engineering, system engineering, and related fields to address the challenges in engineering the next-generation adaptive software systems. The contents of the book range from design and engineering principles (Chap. 1) to control–theoretic solutions (Chap. 2) and bidirectional transformations (Chap. 3), which can be seen as promising ways to implement the functional requirements of self-adaptive systems. Important quality requirements are also dealt with by these approaches: parallel adaptation for performance (Chap. 4), self-adaptive authorization infrastructure for security (Chap. 5), and self-adaptive risk assessment for self-protection (Chap. 6). Finally, Chap. 7 provides a concrete self-adaptive robotics operating system as a testbed for self-adaptive systems. The book grew out of a series of the Shonan Meetings on this ambitious topic held in 2012, 2013, and 2015. The authors were active participants in the meetings and have brought in interesting points of view. After several years of reflection, they now have been able to crystalize the ideas contained herein and collaboratively pave the way for solving some aspects of the research problems. As a result, the book stands as a milestone to initiate further progress in this promising interdisciplinary research field.

A major challenge for modern software systems is to become more cost-effective, while being versatile, flexible, resilient, energy-efficient, customizable, and configurable when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip the software system with self-adaptation capabilities. Despite recent advances in this area, one key aspect that remains to be tackled in depth is the provision of assurances. Originating from a Dagstuhl seminar held in December 2013, this book constitutes the third volume in the series “Software Engineering for Self-Adaptive Systems”, and looks specifically into the provision of assurances. Opening with an overview chapter on Research Challenges, the book presents 13 further chapters written and carefully reviewed by internationally leading researchers in the field. The book is divided into topical sections on research challenges, evaluation, integration and coordination, and reference architectures and platforms.

Although the self-adaptability of systems has been studied in a wide range of disciplines, from biology to robotics, only recently has the software engineering community recognized its key role in enabling the development of self-adaptive systems that are able to adapt to internal faults, changing requirements, and evolving environments. The 15 carefully reviewed papers included in this state-of-the-art survey were presented at the International Seminar on "Software Engineering for Self-Adaptive Systems", held in Dagstuhl Castle, Germany, in October 2010. Continuing the course of the first book of the series on "Software Engineering for Self-Adaptive Systems" the collection of papers in this second volume comprises a research roadmap accompanied by four elaborating working group papers. Next there are two parts - with three papers each - entitled "Requirements and Policies" and "Design Issues"; part four of the book contains four papers covering a wide range of "Applications".

This book, Innovative Trends in Personalized Software Engineering and Information Systems – The Case of Intelligent and Adaptive E-learning Systems, studies the development of personalized and knowledge-based systems with the purpose of developing fully-automated adaptive software, mainly focusing on enhancing digital learning. The authors cover several integral phases of software engineering and their application in the effective implementation of sophisticated learning technology systems. Systems development and systems evaluation, tailored to adaptive e-learning, are examined in depth. More specifically, intelligent and knowledge-based techniques, such as artificial neural networks, fuzzy logic, genetic algorithms, pattern recognition, learning analytics and data mining, as well as evaluation frameworks adapted to digital learning software are presented. This publication will be of interest to scientists from various disciplines, including computer science, artificial intelligence, education and psychology, and will help researchers working in computer science and engineering to build intelligent and adaptive learning technology systems by employing personalization techniques while following the basic concepts of software engineering and information systems. It will also serve as a valuable tool for junior and senior scientists, supporting their research activities in the field of personalized and knowledge-based software engineering, and instructors will be able to use the book as a guide to the effective design and development of intelligent systems in education.

Managing Trade-Offs in Adaptable Software Architectures explores the latest research on adapting large complex systems to changing requirements. To be able to adapt a system, engineers must evaluate different quality attributes, including trade-offs to balance functional and quality requirements to maintain a well-functioning system throughout the lifetime of the system. This comprehensive resource brings together research focusing on how to manage trade-offs and architect adaptive systems in different business contexts. It presents state-of-the-art techniques, methodologies, tools, best practices, and guidelines for developing adaptive systems, and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to, how to architect a system for adaptability, software architecture for self-adaptive systems, understanding and balancing the trade-offs involved, architectural patterns for self-adaptive systems, how quality attributes are exhibited by the architecture of the system, how to connect the quality of a software architecture to system architecture or other system considerations, and more. - Explains software architectural processes and metrics supporting highly adaptive and complex engineering - Covers validation, verification, security, and quality assurance in system design - Discusses domain-specific software engineering issues for cloud-based, mobile, context-sensitive, cyber-physical, ultra-large-scale/internet-scale systems, mash-up, and autonomic systems - Includes practical case studies of complex, adaptive, and context-critical systems

Much of a software architect’s life is spent designing software systems to meet a set of quality requirements. General software quality attributes include scalability, security, performance or reliability. Quality attribute requirements are part of an application’s non-functional requirements, which capture the many facets of how the functional - quirements of an application are achieved. Understanding, modeling and continually evaluating quality attributes throughout a project lifecycle are all complex engineering tasks whichcontinuetochallengethe softwareengineeringscienti ccommunity. While we search for improved approaches, methods, formalisms and tools that are usable in practice and can scale to large systems, the complexity of the applications that the so- ware industry is challenged to build is ever increasing. Thus, as a research community, there is little opportunity for us to rest on our laurels, as our innovations that address new aspects of system complexity must be deployed and validated. To this end the 5th International Conference on the Quality of Software Archit- tures (QoSA) 2009 focused on architectures for adaptive software systems. Modern software systems must often recon guretheir structure and behavior to respond to c- tinuous changes in requirements and in their execution environment. In these settings, quality models are helpful at an architectural level to guide systematic model-driven software development strategies by evaluating the impact of competing architectural choices.

This book focuses on the topic of improving software quality using adaptive control approaches. As software systems grow in complexity, some of the central challenges include their ability to self-manage and adapt at run time, responding to changing user needs and environments, faults, and vulnerabilities. Control theory approaches presented in the book provide some of the answers to these challenges. The book weaves together diverse research topics (such as requirements engineering, software development processes, pervasive and autonomic computing, service-oriented architectures, on-line adaptation of software behavior, testing and QoS control) into a coherent whole. Written by world-renowned experts, this book is truly a noteworthy and authoritative reference for students, researchers and practitioners to better understand how the adaptive control approach can be applied to improve the quality of software systems. Book chapters also outline future theoretical and experimental challenges for researchers in this area.