Write a program that takes any input text and produces both a frequency table and the corresponding Huffman code.
Take approximately 360 words from any English document as your input text. Ignore all blanks, all punctuation marks, all special symbols. Create an input file with this input text.
Construct the frequency table according to the input text read from the file:
The frequency's must be listed, in order, from largest (at the top) to smallest (at the bottom)
Then, using the Huffman algorithm, construct the optimal prefix binary code for the table.
The Huffman codes will be sorted in the same manner as the one above i.e. frequency, highest to lowest.
Design your program to read the input from the input file "infile.dat". Your program must produce the output, in the file "outfile.dat",(Files must be named "infile.dat" and "outfile.dat" consisting of
the frequency table for the source text,
the Huffman code for each letter and digit in the source code, and
the length of the coded message in terms of number of bits,
Final Output (Example Values Not Accurate)
Symbol frequency
A,
15%
m,
11%
7,
6%
Symbol Huffman
Codes
A,
10101
m,
1101
7,
111
Total Bits: 16005
Note: You must not submit your "node_modules" folder if you are working on NodeJs/JavaScript. (Just submit your JavaScript source code and package.json file)
Huffman Coding
Criteria
Ratings
Pts
Prompt user for input file path (if no input from user, assume path: current working directory, file-name: infile.dat)
5.0 pts
0.0 pts
Full
No
5.0 pts
Marks
Marks
Prompt user for output file path. Purge file if exists already, or delete existing contents before writing. (if no input from user, assume
5.0 pts
0.0 pts
Full
No
5.0 pts
path: current working directory, file-name: outfile.dat)
Marks
Marks
Read text from input file. (Ignore blanks, punctuation and symbols while parsing)
10.0 pts
0.0 pts
Full
No
10.0 pts
Marks
Marks
Generate frequency table for every symbol in input text. Write frequency table to output file (in DESC order of frequency) (-5 points for
15.0 pts
0.0 pts
Full
No
15.0 pts
round off values).
Marks
Marks
Generate Huffman codes for every symbol in input text and write to output file (in DESC order of frequency). If frequency table is
20.0 pts
0.0 pts
Full
No
20.0 pts
incorrect, points will be lost on this criterion.
Marks
Marks
Encoding follows Huffman logic: Most frequent symbol has the smallest binary code. If frequency table is incorrect, points will be lost
20.0 pts
0.0 pts
Full
No
20.0 pts
on this criterion.
Marks
Marks
Compute length of coded message in terms of Huffman codes. Write this to output file. If frequency table and/or Huffman codes are
10.0 pts
0.0 pts
Full
No
10.0 pts
incorrect, points will be lost on this criterion -5 points, incorrect bits calculation).
Marks
Marks
Code style (selection of apt data structures, code efficiency, error checking, etc.)
10.0 pts
0.0 pts
Full
No
10.0 pts
Marks
Marks
Output file formatted for easy reading: Tables displayed as matrix, spacing between distinct items (frequency-table, code-table, length
5.0 pts
0.0 pts
Full
No
5.0 pts
of encoded text), etc.
Marks
Marks
Late submission penalty per policy
0.0 pts
0.0 pts
Full
No
0.0 pts
Marks
Marks
Total Points: 100.0
