Computer Science

a special kind of binary tree used to create short binary codes for data, based on how often each piece of data appears

putting a sequence of characters into an agreed format

how often a piece of data appears in a file

Huffman coding

Measurements of storage

The need for compression

Lossy and lossless compression

Compression ratios

Run length encoding

Comparing compression algorithms

Practical applications of compression

In this unit pupils will be introduced to the concept of data compression and why it is needed. The will compare lossy and lossless compression methods and their typical uses. They will have the opportunity to compression methods such as run length encoding (RLE) and Huffman coding.

Data compression

a special kind of binary tree used to create short binary codes

Match each term with its correct description.

Calculate the frequency of each character.

Assign bit sequences based on the tree structure.

Arrange the steps for creating a Huffman tree in the correct order.

What is the main purpose of Huffman coding?

Order the following characters based on their bit sequence length in Huffman coding (shortest to longest).

to reduce the size of repeating sequences of data

What is the purpose of run length encoding?

repeated or extra data that isn’t needed

Which of the following is a characteristic of lossless compression?

What type of data is best suited for run length encoding?

It depends on the amount of redundancy in the data.

Why might run length encoding not always reduce file size?

Data is compressed without losing any information.

What does 'lossless' mean in data compression?

Huffman coding

Lesson outcome