# First mini-project: Binary prefix codes and Huffman’s codes

\$35.00

## Description

I. INTRODUCTION
A binary code is a representation of set of symbols that assigns a distinct bit string—a code word—to every
symbol in the set. A binary prefix code is a binary code where no bit string of the code is a prefix of another. With
a binary prefix code, we can unambiguously decode any string of bits without marks separating the code words.
A binary prefix code can be constructed from any two-tree with the symbols positioned at the leaves of the tree.
Associate a 0 to the left child and a 1 to the right child of every node with children. The code word of a symbol
is the sequence of bits read along the unique path from the root to the leaf holding the symbol. Figure 1 shows a
prefix code and the two-tree from which is was generated.
Suppose that we are given a set of n symbols together with their relative frequencies of occurrence. Let fi and
si denote the relative frequency and code word length, respectively, of symbol ai
, for 1 ≤ i ≤ n. The symbols are
encoded with a binary prefix code. The average length of the code is given by
∑n
i=1
fisi
. (1)
An optimal binary prefix code is a prefix code of minimum average length. David Huffman, in 1951, invented a
method to derive such codes. In his honor, optimal binary prefix codes bear his name. Today, Huffman’s codes are
symbol code word
a 00
b 010
c 011
d 10
e 110
f 111
a d
e f
Code Two-tree representa on
b c
Fig. 1. A prefix code for the set of symbols {a, b, c, d, e}.
2
symbol freq. code word
a 0,22 011
b 0,03 0000
c 0,14 001
d 0,14 010
e 0,41 1
f 0,06 0001
Code Two-tree representa on
b f
d a
e
c
Fig. 2. A Huffman’s code for the set of symbols {a, b, c, d, e}.
widely used to compress data; they are used, for example, in compressing MP3 files. Here is a brief description
of Huffman’s method in prose. The method builds a two-tree with the symbols positioned at the leaves. It starts
with a forest, where each symbol and its associated frequency is the root of a trivial tree with just one node.
At each iteration, the algorithm finds the two trees whose roots have the smallest frequency over all trees in the
current forest. A new node is created having the previous two roots as children, so that a new tree is formed from
the created node and its two children. The frequency of the new node is the sum of the frequencies of its two
children. The algorithm terminates after n − 1 iterations. Figure 2 shows a Huffman’s code and the final two-tree
of Huffman’s method for the same set of symbols as in Figure 1. The average length of the Huffman’s code is
2, 27 whereas, for the same relative frequencies, the average length of the prefix code of Figure 1 is 2, 64.
What you have to do.
• Implement the procedure GenerateCode(Root, Code) that receives as input a two-tree Root with the symbols
at the leaves and produces as output the corresponding binary prefix code Code. Your code should be efficient.
• Implement the procedure Decode(Root, InString, OutString) that receives as input a two-tree Root representing
a binary prefix code and a bit string InString and produces as output the decoded string of symbols OutString.
• Write program PrefixCode that the reads a sequence of symbols from a file (symbols are separated by spaces
or returns) and prints to screen any binary prefix code of your choice for the set of symbols. Then, the program
reads binary strings from the keyboard and prints the decoded string of symbols to the screen.
• Implement procedure HuffmanCode(Symbols, Freq, Code) that receives as input an array Symbols of symbols
and an array Freq with their relative frequencies, and produces as output a Huffman’s code Code for the set
of symbols. Your code should be efficient.
3
• Write a program Huffman that reads a sequence of symbols and their relative frequencies from a file (a symbol
is separated from its frequency by a space or returns; a frequency is separated from the next symbol by spaces
or returns) and prints a Huffman’s code for the set of symbols.
What do you have to deliver, how, and when.
• You have to deliver your code and a report of no more than three pages containing a text explanation of your
algorithms, their pseudo-codes, and a short discussion.
• The code and the report should be sent in a .zip file to my email address with subject p1..zip
where is your group number. You will also have to deliver a printed version of the report.
• The deadline for the .zip file is October 14, 2016, 23:59. The printed report should be delivered in the class
on October 17.
How I will evaluate your assignment.