Computer Science

a recurring trend, relationship, or structure found within a set of data

repeated or extra data that isn’t needed

Run length encoding

Measurements of storage

The need for compression

Lossy and lossless compression

Compression ratios

Huffman coding

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

What type of compression is run length encoding?

What does run length encoding use to reduce file size?

repetitive information that can be removed

Which of the following is an example of run length encoding?

No, it works best with data that has long repeated patterns.

Does run length encoding always reduce file size?

the ratio of the compressed data to the original data

the processing speed of compression algorithms

the ratio of the original data to the compressed data

The file size decreases, but performance may slow down.

What happens when the compression ratio is higher?

What is the term for the file size before compression?

What is the term for the file size after compression?

What does a higher compression ratio require?

What must be considered when selecting a compression algorithm?

Run length encoding

Lesson outcome