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Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occurs; it then uses this table to build up an optimal way of representing each character as a binary string. We call the binary string the codeword for that character. A property of Huffman code is that it is a prefix code, i.e., in Huffman coding, no codeword is a prefix of some other codeword. The advantage of prefix code is that it makes decoding easier, as we do not need to use delimiter between two successive codewords. Given the frequency of each of the character, we can devise a greedy algorithm for finding the optimal Huffman codeword of each of the characters. For details of the greedy algorithm,
In this assignment, we will build a compression library that compress text les using Huffman coding scheme. This library will have two programs: compress, and decompress; compress accepts a text file and produces a compressed representation of that text file; decompress accepts a file that was compressed with the compress program, and recovers the original file.
HOW TO CONSTRUCT A BIVARIATE FREQUENCY DISTRIBUTION
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Input to the compress is a text le with arbitrary size, but for this assignment we will assume that the data structure of the file fits in the main memory of a computer. Output of
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