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.