In this paper, we consider the problem of using disk blocks efficiently in searching graphs that are too large to fit in internal memory. Our model allows a vertex to be represented any number of times on the disk in order to take advantage of redundancy. We give matching upper and lower bounds for complete d-ary trees and d-dimensional grid graphs, as well as for classes of general graphs that intuitively speaking have a close to uniform number of neighbors around each vertex. We also show that for the special case of grid graphs blocked with isothetic hypercubes, there is a provably better speed-up if even a small amount of redundancy is permitted.

A simple algebraic model is proposed fr measuring the relative complexity of programming systems. The appropriateness of this model is illustrated by its use as a framework for the statement and proof of results dealing with coding-independent limitations on the relative complexity of basic algebras.