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The cost of a number of sequential coding search algorithms is analyzed in a systematic manner. These algorithms search code trees, and find use in data compression, error correction, and maximum likelihood sequence estimation. The cost function is made up of the size of and number of accesses to storage. It is found that algorithms that utilize sorting are much more expensive to use than those that do not; metric-first searching regimes are less efficient than breadth-first or depth-first regimes. Cost functions are evaluated using experimental data obtained from data compression and error correction studies.