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COP 5536辅导、辅导C++程序设计、C++编程语言调试 调试Matlab程序|辅导R语言程序
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COP 5536 Fall 2020
Programming Project
Due Date: Nov 27th 2020, 11:55 pm EST
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is
commonly used for lossless data compression. In this project, you will implement the Huffman encoder and
decoder with the following details.
1. Huffman Coding
The first step in this project is to develop a program that generates Huffman codes. The algorithm for this was
discussed in Lecture 7. For this project, you need to evaluate which of the following priority queue structures
gives best performance: Binary Heap, 4-way cache optimized heap (lecture 10 slides 23 and 24), and Pairing
Heap (lecture 15). Write code to generate Huffman trees using these three data structures and then measure
run time using input data of sample_input_large.txt. Use the following code as reference (this is in C++, use a
similar approach if you are using some other programming language):
clock_t start_time;
// binary heap
start_time = clock();
for(int i = 0; i < 10; i++){ //run 10 times on given data set
build_tree_using_binary_heap(freq_table);
} cout << "Time using binary heap (microsecond): " << (clock() - start_time)/10 <<
endl;
// 4-way heap
start_time = clock();
for(int i = 0; i < 10; i++){ //run 10 times on given data set
build_tree_using_4way_heap(freq_table);
} cout << "Time using 4-way heap (microsecond): " << (clock() - start_time)/10 <<
endl;
// pairing heap
start_time = clock();
for(int i = 0; i < 10; i++){ //run 10 times on given data set
build_tree_using_pairing_heap(freq_table);
}
cout << "Time using pairing heap (microsecond): " << (clock() - start_time)/10 << endl;
Once you have determined which data structure gives the best performance, finalize your Huffman code
program using that data structure. The finalized Huffman code program will take as input a frequency table and
output a code table. Include the timings and conclusions in your report. Once the Huffman code program is
finalized, you should proceed to write the encoder and decoder.
2. Encoder
The encoder reads an input file that is to be compressed and generates two output files – the compressed
version of the input file and the code table. Your encoder can follow this diagram:
Input format
Input file name will be given as a command line argument. This file can have up to 100,000,000 lines and each
line will contain an integer in the range of 0 to 999,999. Consider the following input for the rest of the document:
Building frequency table
First step towards Huffman encoding is to build the frequency table for each value in input. As values will be
within 0 to 999999, an array can be used for storing frequency for each value. Frequency mapping for the given
input file is:
0 ==> 4
2245 ==> 4
999999 ==> 2
34 ==> 3
446 ==> 2
2 ==> 1
build Huffman tree and code
table
freq_table
code_table
encoded.bin
encode
data
build
freq
table
Encoder
code_table.txt
Build Huffman tree and code table
Use the data structure with best timing from section 1 to build the Huffman code table. For the sample input
given, one possible Huffman tree and corresponding code table mapping is given below. The code table can be
built from the Huffman tree by doing a traversal of the tree.
2 ==> 000
999999 ==> 001
0 ==> 01
2245 ==> 10
446 ==> 110
34 ==> 111
Huffman tree code table
Encode data
Once the code table is built, it can be used to encode the original input file by replacing each input value by its
code. Please note that the values are not ASCII characters, rather binary values. You can use "ios::binary" flag
in C++, or OutputStream in Java.
0110010011001011010111110111110111001000
Output format
Encoder program has two output files. One is encoded message in binary format. It must be saved as
"encoded.bin". As mentioned in Encode Data phase, output encoded.bin for given data will be:
encoded.bin
0110010011001011010111110111110111001000
Second output is the code table. Each line in this output file will contain value of a leaf node of Huffman tree,
and its code separated by a space. It must be saved as "code_table.txt".
code_table.txt
2 000
999999 001
0 01
2245 10
446 110
34 111
Note: Both "encoded.bin" and "code_table.txt" are NOT unique. They will not be used for grading directly.
However, the size of "encoded.bin" is unique, so this size will be used for grading purpose. "code_table.txt"
will be used by your decoder program to decompress the encoded file.
3. Decoder
The decoder reads two input files - encoded message and code table. The decoder first constructs the decode
tree using the code table. Then the decoded message can be generated from the encoded message using the
decode tree. Your report should include a description of the algorithm used to construct the decode tree from
the code table together with the complexity of this algorithm.
Input format
The decoder takes two input files - encoded message and code table. File names will be given as command line
arguments. The format of these files is the same as the output format of the encoder, so that the output files
of the encoder program can be directly used by the decoder program. Note that the input encoded message
will be in binary format, not ASCII characters. You can use ios::binary flag for C++ or InputStream for Java.
Output format
Output of decoder program is the decoded message. It should be saved as "decoded.txt". The format of this file
is same as the input format for the encoder. For any sample input, the following scenario should be true:
decoded.txt
4. Files provided in elearning
sample1/..
i. sample_input_small.txt
ii. encoded.bin
iii. code_table.txt iv.
decoded.txt
;inputs/outputs mentioned in this document
sample2/.. ;large inputs/outputs set
i. sample_input_large.txt
ii. encoded.bin
iii. code_table.txt iv.
decoded.txt
;use this file for performance measurement
COP5536_FA20_Project.pdf ;this file
5. Run environment
Your code must be able to run in the linux environment. You can test your program either on CISE
storm.cise.ufl.edu or thunder.cise.ufl.edu server (for which you need to login using your CISE account). Write
a Makefile so that we can build your code using following command at terminal:
$ make
This command should produce two binary files: encoder and decoder.
As mentioned before, encoder should take one input file. We will run it using following command:
$ ./encoder
[For C++]
$ java encoder
[For Java]
Running encoder program must produce the output files with exact name "encoded.bin" and "code_table.txt".
On the other hand, decoder will take two input files. We will run it using following command:
$ ./decoder
[For C++]
$ java decoder
[For Java]
Running decoder program must produce output file with exact name "decoded.txt". Any
violation of these rules will incur 25% penalty.
6. Submission
Your submission must contain the following files:
1. Makefile: To build your program.
2. Your source codes. Do not use any subdirectory.
3. Report.pdf:
a. Should be in pdf format.
b. Should contain your name and UFID.
c. Present function prototypes and structure of your program.
d. Include performance measurement results and explanation.
e. Include what decoding algorithm you used and its complexity.
To submit, compress all your files together into LastName_FirstName.zip and upload to elearning. Please do not
submit directly to a TA. All email submissions will be ignored without further notification. Please note that the
due date is a hard deadline. No late submission will be allowed.
7.Grading Policy
1. Report: 30%
2. Performance Analysis: 10%
3. Correct implementation and execution: 60% Correctness will be tested by:
a. For encoder only: Size of encoded message
b. For decoder only: Correctness of decoded message
c. For both encoder and decoder: Input message => encoder => decoder => output message. Output
message should be same as input message
8. Others
• For C++ and Java, do not use any standard library container other than vector. You must implement all
three types of priority queue by yourself.
• Again, go through the Run Environment section and make sure your program does exactly as required.
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