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Two basic approaches to the cluster counting task in the percolation andrelated models are discussed. The Hoshen-Kopelman multiple labeling techniquefor cluster statistics is redescribed. Modifications for random and aperiodiclattices are sketched as well as some parallelised versions of the algorithmare mentioned. The graph-theoretical basis for the spanning tree approaches isgiven by describing the "breadth-first search" and "depth-first search"procedures. Examples are given for extracting the elastic and geometric"backbone" of a percolation cluster. An implementation of the "pebble game"algorithm using a depth-first search method is also described.Comment: LaTeX, uses ijmpc1.sty(included), 18 pages, 3 figures, submitted to  Intern. J. of Modern Physics

Cluster Counting: The Hoshen–Kopelman Algorithm Versus Spanning Tree Approaches