Algorithms in a Nutshell

Principle: Add Storage to Increase Performance

Many of the computations carried out by the algorithms are optimized by storing information that reflects the results of past computations. Prim's Algorithm for computing the minimum spanning tree for a graph uses a priority queue to store the unvisited vertices in order of their shortest distance to an initial vertex s. During a key step in the algorithm, one must determine whether a given vertex has already been visited. Because the binary heap implementation of the priority queue fails to provide this operation, a separate Boolean array inQueue is maintained to record the status of each vertex. In the same algorithm, a duplicate key array stores the computed distances to avoid having to search again through the priority queue. This extra storage on the order of O(n) is required to ensure the efficient implementation of the algorithm. In most situations, as long as the overhead is O(n), you are going to be safe.

Sometimes an entire computation can be cached to ensure that it never needs to be recomputed. In Chapter 6, we discussed how the hash function for the java.lang.String class stores the computed hash value to speed up its performance.

Sometimes the nature of the input set demands a large amount of storage, such as the dense graphs described in Chapter 6. By using a two-dimensional matrix to store the edge information—rather than using simple adjacency lists—certain algorithms exhibit reasonable performance. Also, you may note ...