  As the complexity and heterogeneity of a system grows, the challenge of
specifying, documenting and synthesizing correct, machine readable designs
increases dramatically. Separation of the system into manageable parts is
needed to support analysis at various levels of granularity so that the system
is maintainable and adaptable over its life cycle. In this paper, we argue that
operads provide an effective knowledge representation to address these
challenges. Formal documentation of a syntactically correct complex design is
built up during design synthesis, while semantic reasoning about which designs
are effective guides the process. Throughout, the ability to break down the
system into parts and reconstitute the whole is maintained. We describe recent
progress in effective modeling under this paradigm and directions for future
work to systematically address scalability challenges for complex system
design.
