Emergent software systems

Contemporary software systems often have millions of lines of code that interact over complex infrastructures. The development of such systems is very challenging due to the increasing complexity of services and the high level of dynamism of current operating environments. In order to support the development and management of such systems, autonomic computing concepts have gained significant importance. The majority of autonomic computing approaches show significant levels of expert dependency in designing adaptive solutions. These approaches usually rely on human-made models and policies to support and guide software adaptation at runtime. These approaches mainly suffer from: i) a significant upfront effort demanded to create such solutions, which adds to the complexity of creating autonomous systems, and ii) unreliability given the high levels of uncertainty in current operating environments, leading the system to degraded performance and error states when subjected to unpredicted operating conditions and unexpected software interactions. Motivated by the problems and limitations of state-of-the-art autonomic computing solutions, this thesis introduces the concept of Emergent Software Systems. These systems are autonomously composed at runtime from discovered components, and are autonomously optimised based on the operating conditions, being able to build their own understanding of their environment and constituent parts. This thesis defines Emergent Software Systems, presenting the challenges of implementing such approach, and presents a fully functioning emergent systems framework that demonstrates this concept in real-world, fully functioning datacentre-based software