Integration science: more than putting pieces together

Abstract

In this paper, we describe our wrapping technique for dynamic in complex heterogeneous systems, which is based on explicit, machine-interpretable descriptions of all software, hardware, and other computational resources in a constructed complex system, and active processes that select, adapt, and combine these resources for particular problems. We describe our problem posing interpretation of programming languages, which uses knowledge-based polymorphism to unify the interpretation of all programming languages, and the wrex notation for generic programming, and show how they apply to several difficult system engineering problems. We describe our activities in support of the development of integration science, which will collect principles and powerful analytical methods to augment the present state-of-the-art. We also claim that the requirements for dual use of computational components are much more stringent than simple system processes would have us believe, and show how our wrapping approach to knowledge-based supports those requirements.