Abstract. Previous workshops related to aspect oriented software development, reflection organized at previous ECOOP conferences (e.g., RMA’00 1 and AOM-MeT’01 2) and conferences on the same topics (Reflection’01 and AOSD since 2002) have pointed out the growing interest on these topics and their relevance in the software evolution as techniques for code instrumentation. Very similar conclusions can be drawn by reading the contributions to the workshops on unanticipated software evolution (USE 2002 and USE 2003 3). Following the example provided by these venues, the RAM-SE (Reflection, AOP and Meta-Data for Software Evolution) workshop has provided an opportunity for researchers with a broad range of interests in reflective techniques and aspectoriented software development to discuss recent developments of such a techniques in application to the software evolution. The workshop main goal was to encourage people to present works in progress. These works could cover all the spectrum from theory to practice. To ensure creativity, originality, and audience interests, participants have been selected by the workshop organizers on the basis of 5-page position paper. We hope that the workshop will help them to mature their ideas and to improve the quality of their future publications based on the presented work.

The heterogeneous, large-scale and decentralised nature of peerto-peer systems creates significant issues when deploying new functionality and adapting peer behaviour. The ability to autonomously deploy new adaptive functionality is therefore highly beneficial. This paper investigates middleware support for evolving and adapting peers in divergent systems through reflective component based design. This approach allows selfcontained functionality to exist in the network as a primary entity. This functionality is autonomously propagated to suitable peers, allowing nodes to be evolved and adapted to their individual constraints and the specific requirements of their environment. This results in effective functionality flourishing whilst suboptimal functionality dies out. By this, a self-managed infrastructure is created that supports the deployment of functionality following the evolutionary theory of natural selection. This approach is evaluated through simulations to highlight the potential of using natural selection for the deployment and management of software evolution.