Algorithms [Sedgewick, Robert]

22. File Compression

For the most part, the algorithms that we have studied have been designed primarily to use as little time as possible and only secondarily to conserve space. In this section, we’ll examine some algorithms with the opposite orientation: methods designed primarily to reduce space consumption without using up too much time. Ironically, the techniques that we’ll examine to save space are “coding” methods from information theory which were developed to minimize the amount of information necessary in communications

systems and therefore originally intended to save time (not space).

In general, most files stored on computer systems have a great deal of redundancy. The methods we will examine save space by taking advantage of the fact that most files have a relatively low “information content.” File compression techniques are often used for text files (in which certain characters appear much more often than others), “raster” files for encoding pictures (which can have large homogeneous areas), and files for the digital representation of sound and other analog signals (which can have large repeated patterns).

We’ll look at an elementary algorithm for the problem (which is still quite useful) and an advanced “optimal” method. The amount of space saved by these methods will vary depending on characteristics of the file. Savings of 20% to 50% are typical for text files, and savings of 50% to 90% might be achieved for binary files. For some types of files, for example files consisting of random bits, little can be gained. In fact, it is interesting to note that any general-purpose compression method must make some files longer (otherwise we could continually apply the method to produce an arbitrarily small file).

On one hand, one might argue that file compression techniques are less important than they once were because the cost of computer storage devices has dropped dramatically and far more storage is available to the typical user than in the past. On the other hand, it can be argued that file compression

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