Software self-adaptability by means of artificial evolution

Abstract

Contemporary distributed software systems are reaching extremely high complexity levels which exceeds complexities of known engineering problems to date. Especially open heterogeneous multi-agent systems which may potentially be spread all around the globe, interacting with different changing web-services and web-technologies are exposed to demanding, dynamic and highly unpredictable environments. Traditional control-based handling of adaptability may not be suitable anymore, therefore there is a tendency for exploring different adaptability models inspired by natural/biological phenomena. In this article we review overall design of an adaptive software system based on a simple model of artificial evolution. We propose a new paradigm for handling complexity in dynamic environments based on a theory of self-producing self-adaptive software systems. We have substantial evidence to believe that a bottomup approach based on self-production and self-maintenance may help to build more robust and more flexible self-adapting software systems. This paper introduces the new framework, provides analysis of some results, implications and future research directions toward a complete and selfcontained theory of evolvable and self-adaptable software systems. © Springer-Verlag 2004.