Self-adaptive software is a closed-loop system that tries to manage, direct, or regulate its own behavior dynamically. Such a system aims at providing an automated and systematic approach to handling the increasing complexity of operation management. Mission-critical systems (e.g., e-business and telecommunication systems) are usually large, complex, and distributed. These systems must preserve their Quality of Service (QoS) at runtime under highly dynamic and non-deterministic conditions; therefore, they are suitable candidates for being equipped with self-adaptive capabilities. Although significant efforts have been devoted to modeling, designing, developing and deploying self-adaptive software since a decade ago, there is still a lack of well-established concrete processes for evaluating such systems. This dissertation proposes a systematic evaluation process for mission-critical self-adaptive software systems. The process is a well-defined testing approach that needs a post-mortem analysis, takes the quantified QoS requirements as inputs, and comprises two main phases: i) conducting system-level testing, and ii) evaluating QoS requirements satisfaction. The process uses Service Level Agreements (SLAs) as quantified QoS requirements, and consequently as the adaptation requirements of mission-critical systems. Adaptation requirements are specific types of requirements used to engineer self-adaptive software. Moreover, for the first phase, the dissertation discusses the uniqueness and necessity of conducting system-level load and stress testing on a self-adaptive software system, for collecting runtime QoS data. In the second phase, the process makes use of utility functions to generate a single value indicating the QoS satisfaction of the evaluated system. The dissertation mainly focuses on evaluating the performance, availability and reliability characteristics of QoS. An open source service-oriented Voice over IP (VoIP) application was selected as a case study. The VoIP application was transformed into a self-adaptive software system with various types of adaptation mechanisms. A set of empirical experiments was performed on the developed self-adaptive VoIP application, and the proposed process was adopted for evaluating the effectiveness of different adaptation mechanisms. To this end, the dissertation defines a sample SLA for the VoIP application, presents a report on the load and stress testing performed on the self-adaptive VoIP application, and presents a set of utility functions for evaluation. The experiments illustrate the validity, reliability, flexibility, and cost of the proposed evaluation process. In sum, this dissertation introduces a novel evaluation process for mission-critical self-adaptive software systems, and shows that the proposed process can help researchers to systematically evaluate their self-adaptive systems.

Self-adaptive software is a closed-loop system that tries to manage, direct, or regulate its own behavior dynamically. Such a system aims at providing an automated and systematic approach to handling the increasing complexity of operation management. Mission-critical systems (e.g., e-business and telecommunication systems) are usually large, complex, and distributed. These systems must preserve their Quality of Service (QoS) at runtime under highly dynamic and non-deterministic conditions; therefore, they are suitable candidates for being equipped with self-adaptive capabilities. Although significant efforts have been devoted to modeling, designing, developing and deploying self-adaptive software since a decade ago, there is still a lack of well-established concrete processes for evaluating such systems. This dissertation proposes a systematic evaluation process for mission-critical self-adaptive software systems. The process is a well-defined testing approach that needs a post-mortem analysis, takes the quantified QoS requirements as inputs, and comprises two main phases: i) conducting system-level testing, and ii) evaluating QoS requirements satisfaction. The process uses Service Level Agreements (SLAs) as quantified QoS requirements, and consequently as the adaptation requirements of mission-critical systems. Adaptation requirements are specific types of requirements used to engineer self-adaptive software. Moreover, for the first phase, the dissertation discusses the uniqueness and necessity of conducting system-level load and stress testing on a self-adaptive software system, for collecting runtime QoS data. In the second phase, the process makes use of utility functions to generate a single value indicating the QoS satisfaction of the evaluated system. The dissertation mainly focuses on evaluating the performance, availability and reliability characteristics of QoS. An open source service-oriented Voice over IP (VoIP) application was selected as a case study. The VoIP application was transformed into a self-adaptive software system with various types of adaptation mechanisms. A set of empirical experiments was performed on the developed self-adaptive VoIP application, and the proposed process was adopted for evaluating the effectiveness of different adaptation mechanisms. To this end, the dissertation defines a sample SLA for the VoIP application, presents a report on the load and stress testing performed on the self-adaptive VoIP application, and presents a set of utility functions for evaluation. The experiments illustrate the validity, reliability, flexibility, and cost of the proposed evaluation process. In sum, this dissertation introduces a novel evaluation process for mission-critical self-adaptive software systems, and shows that the proposed process can help researchers to systematically evaluate their self-adaptive systems.

The complexity of software systems is exploding, along with their use and application in new domains. Managing this complexity has become a focal point for research in Software Engineering. One direction for research in this area is developing techniques for designing adaptive software systems that self-optimize, self-repair, self-configure and self-protect, thereby reducing maintenance costs, while improving quality of service. This thesis presents a requirements-driven approach for developing adaptive and customizable systems. Requirements goal models are used as a basis for capturing problem variability, leading to software designs that support a space of possible behaviours – all delivering the same functionality. This space can be exploited at system deployment time to customize the system on the basis of user preferences. It can also be used at runtime to support system adaptation if the current behaviour of the running system is deemed to be unsatisfactory. The contributions of the thesis include a framework for systematically generating designs from high-variability goal models. Three complementary design views are generated: configurational view (feature model), behavioural view (statecharts) and an architectural view (parameterized architecture). The framework is also applied to the field of business process management for intuitive high-level process customization. In addition, the thesis proposes a modeling framework for capturing domain variability through contexts and applies it to goal models. A single goal model is used to capture requirements variations in different contexts. Models for particular contexts can then be automatically generated from this global requirements model. As well, the thesis proposes a new class of requirements-about-requirements called awareness requirements. Awareness requirements are naturally operationalized through feedback controllers – the core mechanisms of every adaptive system. The thesis presents an approach for systematically designing monitoring, analysis/diagnosis, and compensation components of a feedback controller, given a set of awareness requirements. Situations requiring adaptation are explicitly captured using contexts.

The complexity of software systems is exploding, along with their use and application in new domains. Managing this complexity has become a focal point for research in Software Engineering. One direction for research in this area is developing techniques for designing adaptive software systems that self-optimize, self-repair, self-configure and self-protect, thereby reducing maintenance costs, while improving quality of service. This thesis presents a requirements-driven approach for developing adaptive and customizable systems. Requirements goal models are used as a basis for capturing problem variability, leading to software designs that support a space of possible behaviours – all delivering the same functionality. This space can be exploited at system deployment time to customize the system on the basis of user preferences. It can also be used at runtime to support system adaptation if the current behaviour of the running system is deemed to be unsatisfactory. The contributions of the thesis include a framework for systematically generating designs from high-variability goal models. Three complementary design views are generated: configurational view (feature model), behavioural view (statecharts) and an architectural view (parameterized architecture). The framework is also applied to the field of business process management for intuitive high-level process customization. In addition, the thesis proposes a modeling framework for capturing domain variability through contexts and applies it to goal models. A single goal model is used to capture requirements variations in different contexts. Models for particular contexts can then be automatically generated from this global requirements model. As well, the thesis proposes a new class of requirements-about-requirements called awareness requirements. Awareness requirements are naturally operationalized through feedback controllers – the core mechanisms of every adaptive system. The thesis presents an approach for systematically designing monitoring, analysis/diagnosis, and compensation components of a feedback controller, given a set of awareness requirements. Situations requiring adaptation are explicitly captured using contexts.

Self-adaptive software systems are increasingly in demand. The driving forces are changes in the software “self” and “context”, particularly in distributed and pervasive applications. These systems provide self-* properties in order to keep requirements satisfied in different situations. Engineering self-adaptive software normally involves building the adaptable software and the adaptation manager. This PhD thesis focuses on the latter, especially on the design and implementation of the deciding process in an adaptation manager. For this purpose, a Quality-driven Framework for Engineering an Adaptation Manager (QFeam) is proposed, in which quality requirements play a key role as adaptation goals. Two major phases of QFeam are building the runtime adaptation model and designing the adaptation mechanism. The modeling phase investigates eliciting and specifying key entities of the adaptation problem space including goals, attributes, and actions. Three composition patterns are discussed to link these entities to build the adaptation model, namely: goal-centric, attribute-action-coupling, and hybrid patterns. In the second phase, the adaptation mechanism is designed according to the adopted pattern in the model. Therefore, three categories of mechanisms are discussed, in which the novel goal-ensemble mechanism is introduced. A concrete model and mechanism, the Goal-Attribute-Action Model (GAAM), is proposed based on the goal-centric pattern and the goal-ensemble mechanism. GAAM is implemented based on the StarMX framework for Java-based systems. Several considerations are taken into account in QFeam: i) the separation of adaptation knowledge from application knowledge, ii) highlighting the role of adaptation goals, and iii) modularity and reusability. Among these, emphasizing goals is the tenet of QFeam, especially in order to address the challenge of addressing several self- * properties in the adaptation manager. Furthermore, QFeam aims at embedding a model in the adaptation manager, particularly in the goal-centric and hybrid patterns. The proposed framework focuses on mission-critical systems including enterprise and service-oriented applications. Several empirical studies were conducted to put QFeam into practice, and also evaluate GAAM in comparison with other adaptation models and mechanisms. Three case studies were selected for this purpose: the TPC-W bookstore application, a news application, and the CC2 VoIP call controller. Several research questions were set for each case study, and findings indicate that the goal-ensemble mechanism and GAAM can outperform or work as well as a common rule-based approach. The notable difference is that the effort of building an adaptation manager based on a goal-centric pattern is less than building it using an attribute-action-coupling pattern. Moreover, representing goals explicitly leads to better scalability and understandability of the adaptation manager. Overall, the experience of working on these three systems show that QFeam improves the design and development process of the adaptation manager, particularly by highlighting the role of adaptation goals.

Self-adaptive software systems are increasingly in demand. The driving forces are changes in the software “self” and “context”, particularly in distributed and pervasive applications. These systems provide self-* properties in order to keep requirements satisfied in different situations. Engineering self-adaptive software normally involves building the adaptable software and the adaptation manager. This PhD thesis focuses on the latter, especially on the design and implementation of the deciding process in an adaptation manager. For this purpose, a Quality-driven Framework for Engineering an Adaptation Manager (QFeam) is proposed, in which quality requirements play a key role as adaptation goals. Two major phases of QFeam are building the runtime adaptation model and designing the adaptation mechanism. The modeling phase investigates eliciting and specifying key entities of the adaptation problem space including goals, attributes, and actions. Three composition patterns are discussed to link these entities to build the adaptation model, namely: goal-centric, attribute-action-coupling, and hybrid patterns. In the second phase, the adaptation mechanism is designed according to the adopted pattern in the model. Therefore, three categories of mechanisms are discussed, in which the novel goal-ensemble mechanism is introduced. A concrete model and mechanism, the Goal-Attribute-Action Model (GAAM), is proposed based on the goal-centric pattern and the goal-ensemble mechanism. GAAM is implemented based on the StarMX framework for Java-based systems. Several considerations are taken into account in QFeam: i) the separation of adaptation knowledge from application knowledge, ii) highlighting the role of adaptation goals, and iii) modularity and reusability. Among these, emphasizing goals is the tenet of QFeam, especially in order to address the challenge of addressing several self- * properties in the adaptation manager. Furthermore, QFeam aims at embedding a model in the adaptation manager, particularly in the goal-centric and hybrid patterns. The proposed framework focuses on mission-critical systems including enterprise and service-oriented applications. Several empirical studies were conducted to put QFeam into practice, and also evaluate GAAM in comparison with other adaptation models and mechanisms. Three case studies were selected for this purpose: the TPC-W bookstore application, a news application, and the CC2 VoIP call controller. Several research questions were set for each case study, and findings indicate that the goal-ensemble mechanism and GAAM can outperform or work as well as a common rule-based approach. The notable difference is that the effort of building an adaptation manager based on a goal-centric pattern is less than building it using an attribute-action-coupling pattern. Moreover, representing goals explicitly leads to better scalability and understandability of the adaptation manager. Overall, the experience of working on these three systems show that QFeam improves the design and development process of the adaptation manager, particularly by highlighting the role of adaptation goals.

There is a strong synergy between the concepts of evolution and adaptation in software engineering: software adaptation refers to both the current software being adapted and to the evolution process that leads to the new adapted software. Evolution changes for the purpose of adaptation are usually made at development or compile time, and are meant to handle predictable situations in the form of software change requests. On the other hand, software may also change and adapt itself based on the changes in its environment. Such adaptive changes are usually dynamic, and are suitable for dealing with unpredictable or temporary changes in the software's operating environment. A promising solution for software adaptation is to develop self-adaptive software systems that can manage changes dynamically at runtime in a rapid and reliable way. One of the main advantages of self-adaptive software is its ability to manage the complexity that stems from highly dynamic and nondeterministic operating environments. If a self-adaptive software system has been engineered and used properly, it can greatly improve the cost-effectiveness of software change through its lifespan. However, in practice, many of the existing approaches towards self-adaptive software are rather expensive and may increase the overall system complexity, as well as subsequent future maintenance costs. This means that in many cases, self-adaptive software is not a good solution, because its development and maintenance costs are not paid off. The situation is even worse in the case of making current (legacy) systems adaptive. There are several factors that have an impact on the cost-effectiveness and usability of self-adaptive software; however the main objective of this thesis is to make a software system adaptive in a cost-effective way, while keeping the target adaptive software generic, usable, and evolvable, so as to support future changes. In order to effectively engineer and use self-adaptive software systems, in this thesis we propose a new conceptual model for identifying and specifying problem spaces in the context of self-adaptive software systems. Based on the foundations of this conceptual model, we propose a model-centric approach for engineering self-adaptive software by designing a generic adaptation framework and a supporting evolution process. This approach is particularly tailored to facilitate and simplify the process of evolving and adapting current (legacy) software towards runtime adaptivity. The conducted case studies reveal the applicability and effectiveness of this approach in bringing self-adaptive behaviour into non-adaptive applications that essentially demand adaptive behaviour to sustain.

This study investigates the concept of adaptivity in relation to the evolution of software and hence software embedded products. Whilst laying out the benefits of adaptivity in products, it discusses the potential future threats engendered by the actual change observed in the functionality principles of adaptive products. The discussion is based upon cybernetic theory which defines control technology in the 20th century anew. Accordingly, literature survey on cybernetic theory, evolution of software from conventional to adaptive structure is presented. The changes in the functionality principles of adaptive systems and the similarities that these changes show with living autonomous systems is also investigated. The roles of product and user are redefined in relation to changing control mechanisms. Then, the new direction that the conventional product-user relationship has taken with adaptive products is examined. Finally, the potential future threats this new direction might bring is discussed with the help of two control conflict situations.

Our research posits a context-sensitive, adaptable, assistive services and technology system (CAAST) that takes advantage of the advancements in mobile computing to provide barrier-free access to environmental information and devices. To inform our research we explore the following topics: the deficiencies associated with current assistive technologies; the advances in wireless sensor node technology; the interference and accuracy problems associated with wireless location detection; the coordination problems associated with service discovery; the management and coordination problems associated with decentralized sensor nodes; the separation of information and activities from the human interface; the efficiency and abstraction problems associated with interface description languages; and the adaptation of information and activities to meet the needs of those with disabilities. As a result of our research into these areas we devise an assistive technology, CAAST, that intends to be a comprehensive approach to universal access to information and activities for those with disabilities. / Department of Computer Science

There is a strong synergy between the concepts of evolution and adaptation in software engineering: software adaptation refers to both the current software being adapted and to the evolution process that leads to the new adapted software. Evolution changes for the purpose of adaptation are usually made at development or compile time, and are meant to handle predictable situations in the form of software change requests. On the other hand, software may also change and adapt itself based on the changes in its environment. Such adaptive changes are usually dynamic, and are suitable for dealing with unpredictable or temporary changes in the software's operating environment. A promising solution for software adaptation is to develop self-adaptive software systems that can manage changes dynamically at runtime in a rapid and reliable way. One of the main advantages of self-adaptive software is its ability to manage the complexity that stems from highly dynamic and nondeterministic operating environments. If a self-adaptive software system has been engineered and used properly, it can greatly improve the cost-effectiveness of software change through its lifespan. However, in practice, many of the existing approaches towards self-adaptive software are rather expensive and may increase the overall system complexity, as well as subsequent future maintenance costs. This means that in many cases, self-adaptive software is not a good solution, because its development and maintenance costs are not paid off. The situation is even worse in the case of making current (legacy) systems adaptive. There are several factors that have an impact on the cost-effectiveness and usability of self-adaptive software; however the main objective of this thesis is to make a software system adaptive in a cost-effective way, while keeping the target adaptive software generic, usable, and evolvable, so as to support future changes. In order to effectively engineer and use self-adaptive software systems, in this thesis we propose a new conceptual model for identifying and specifying problem spaces in the context of self-adaptive software systems. Based on the foundations of this conceptual model, we propose a model-centric approach for engineering self-adaptive software by designing a generic adaptation framework and a supporting evolution process. This approach is particularly tailored to facilitate and simplify the process of evolving and adapting current (legacy) software towards runtime adaptivity. The conducted case studies reveal the applicability and effectiveness of this approach in bringing self-adaptive behaviour into non-adaptive applications that essentially demand adaptive behaviour to sustain.