COS 226 Programming Assignment

Burrows-Wheeler Data Compression Algorithm

Implement the Burrows-Wheeler data compression algorithm. This revolutionary algorithm outcompresses gzip and PKZIP, is relatively easy to implement, and is not protected by any patents. It forms the basis of the Unix compression utililty bzip2.

The Burrows-Wheeler compression algorithm consists of three different algorithmic components, which are applied in succession:

  1. Burrows-Wheeler transform. Given a typical English text file, transform it into a text file in which sequences of the same character occur near each other many times.

  2. Move-to-front encoding. Given a text file in which sequences of the same character occur near each other many times, convert it into a text file in which certain characters appear more frequently than others.

  3. Huffman compression. Given a text file in which certain characters appear more frequently than others, compress it by encoding freqently occuring characters with short codewords and rare ones with long codewords.
The only step that compresses the message is the final step. The final step is particularly effective because the first two steps result in a text file in which certain characters appear much more frequently than others. To expand a message, apply the inverse operations in reverse order: first apply the Huffman expansion, then the move-to-front decoding, and finally the inverse Burrows-Wheeler transform.

Binary input and binary output. To enable that your programs work with binary data, you will use the libraries BinaryStdIn.java and BinaryStdOut.java described in lecture and Algorithms 4. To display the binary output, you can use HexDump.java, which takes a command-line argument N, reads bytes from standard input and writes them to standard output in hexadecimal, N per line.

% more abra.txt
ABRACADABRA!

% java HexDump 16 < abra.txt
41 42 52 41 43 41 44 41 42 52 41 21
12 bytes
Note that 'A' is 41 (hex) in ASCII.

Huffman encoding and decoding. Huffman.java implements the classic Huffman compression and expansion algorithms from lecture and Algorithms 4.

% java Huffman - < abra.txt | java HexDump 16
50 4a 22 43 43 54 a8 40 00 00 01 8f 96 8f 94
15 bytes
% java Huffman - < abra.txt | java Huffman +
ABRACADABRA!

Move-to-front encoding and decoding. The main idea of move-to-front encoding is to maintain an ordered sequence of all of the characters, and repeatedly read in characters from the input message, print out the position in which that character appears, and move that character to the front. As a simple example, if the initial ordering over a 6-character alphabet is A B C D E F, and we want to encode the input CAAABCCCACCF, then we would update the move-to-front sequences as follows:

move-to-front    in   out
-------------    ---  ---
 A B C D E F      C    2 
 C A B D E F      A    1
 A C B D E F      A    0
 A C B D E F      A    0
 A C B D E F      B    2
 B A C D E F      C    2
 C B A D E F      C    0
 C B A D E F      C    0
 C B A D E F      A    2
 A C B D E F      C    1
 C A B D E F      C    0
 C A B D E F      F    5
 F C A B D E  
If the same character occurs next to each other many times in the input, then many of the output values will be small integers, such as 0, 1, and 2. The extremely high frequency of certain characters makes an ideal scenario for Huffman coding. Name your program MoveToFront.java and organize it using the following API:
public class MoveToFront {
    // apply move-to-front encoding, reading from standard input and writing to standard output
    public static void encode()

    // apply move-to-front decoding, reading from standard input and writing to standard output
    public static void decode()

    // if args[0] is '-', apply move-to-front encoding
    // if args[0] is '+', apply move-to-front decoding
    public static void main(String[] args)
}

Burrows-Wheeler transform. The goal of the Burrows-Wheeler transform is not to compress a message, but rather to transform it into a form that is more amenable to compression. The transform rearranges the characters in the input so that there are lots of clusters with repeated characters, but in such a way that it is still possible to recover the original input. It relies on the following intuition: if you see the letters hen in English text, then most of the time the letter preceding it is t or w. If you could somehow group all such preceding letters together (mostly t's and some w's), then you would have an easy opportunity for data compression.

Name your program BurrowsWheeler.java and organize it using the following API:
public class BurrowsWheeler {
    // apply Burrows-Wheeler encoding, reading from standard input and writing to standard output
    public static void encode()

    // apply Burrows-Wheeler decoding, reading from standard input and writing to standard output
    public static void decode()

    // if args[0] is '-', apply Burrows-Wheeler encoding
    // if args[0] is '+', apply Burrows-Wheeler decoding
    public static void main(String[] args)
}

Analysis. Once you have MoveToFront.java and BurrowsWheeler.java working, compress some of these text files. Compression consists of BurrowsWheeler, MoveToFront and Huffman all together. Also try it on some binary files. Calculate the compression ratio achieved for each file. Also, report the time to compress and decompress each file. Finally, determine the order of growth of the running time of each of your encoders and decoders.

Deliverables. Submit MoveToFront.java and BurrowsWheeler.java along with any other helper files needed to run your program (excluding those in algs4.jar and stdlib.jar). Also submit a readme.txt and answer all questions.

This assignment was developed by Kevin Wayne.
Copyright © 2004.