Huffman Tree Encoding + URL Request
[](https://travis-ci.com/MiraCostaCS-Nery/cs113-hw08-huffmantree-aguilaraul)
> One of the earliest forms of data compression was through Morse code, which allowed for the transmission of textual information over a wire. Each letter has been encoded based on its typical frequency of occurrence, with more common letters receiving shorter messages (such as the letter 'e' being represented as a single dot). A later version of data compression, called Huffman encoding, arose with the rise of the internet in the 1970s. Being dynamically generated on input data, Huffman encoding was an efficient means of data compression until the invention of the LZ77 algorithm in 1977.
## Huffman Tree Encoder
You will be given some code that will retrieve text from a given website and output it to a file (see the following table for limited chars), as well as the code for a Binary Tree. You are to use Java’s built in `PriorityQueue`, in conjunction with the given `BinaryTree` and `HuffmanInterface` to build a `HuffmanTree` which will encode the retrieved text file. Your `HuffmanTree` implementation will provide a lossless compression of text which can then be sent (along with the Huffman tree) and decompressed with the same Huffman tree.
```
Valid chars left over after cleaning webpage and storing into file:
A-Z (upper case letter) characters
a-z (lower case letter) characters
0-9 (digit) characters
only allowed symbols: space ( ), tab (\t), newline (\n), exclamation mark (!), period (.), question mark (?)
```
**Provide a driver** to demonstrate your `HuffmanTree` implementation works by:
1. Taking a URL and output text file name to create the ***original file***, this file is used to create the Huffman tree
2. Using the built Huffman tree with the *original file*'s website text to create an ***encoded file***
3. Using the built Huffman tree with the *encoded file* to create a ***decoded file***
4. Output the number of bits for each file, make sure to use 16 bits per character for the *original* and *decoded* files (for *encoded* file simply count the number of 0's and 1's for the number of bits). Note that *original* and *decoded* files should have the exact same number of bits!
5. Output the percentage of compression (number of bits in *original* file / number of bits in *encoded* file).
