Computer Science - 9210 OxfordAQA

Data Compression

Muhtasari

Write out the word BANANA in ordinary character codes and it takes 42 bits. Write it out cleverly and it takes 9. Nothing has been thrown away, nothing has been approximated, and the original word can be reconstructed exactly. The saving comes from noticing something the plain encoding ignores: the letter A turns up three times as often as the letter B, and a code that gives A a shorter pattern than B will win.

This lesson covers what data compression is, why it is worth doing, and the two methods this specification examines. You will learn to write data as run length encoding pairs, to build a Huffman tree from a string and read the codes off it, to interpret a tree somebody else has given you, and to calculate exactly how many bits each method saves against plain 7-bit ASCII. You will also learn the situation in which compression makes a file larger, which is a real result and a favourite of examiners.

Malengo

  1. Explain what data compression is.
  2. Understand why data may be compressed and that there are different ways to compress data. Explain how data can be compressed using Huffman coding. Be able to build a Huffman tree.
  3. Be able to interpret a Huffman tree.
  4. Calculate the number of bits required to store a piece of data compressed using Huffman coding.
  5. Calculate the number of bits required to store a piece of uncompressed data in ASCII.
  6. Explain how data can be compressed using run length encoding (RLE).
  7. Represent data in RLE frequency/data pairs.

Ramani ya mawazo

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Maelezo ya Somo

Data compression is the process of encoding data so that it uses fewer bits than it did before, while still representing the same information. The word same is doing real work in that sentence: the methods on this specification are both able to reproduce the original data exactly, so nothing is approximated or discarded. Compressing and then decompressing gets you back precisely what you started with.

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Tathmini ya Somo

Hongera kwa kukamilisha somo la Data Compression. Sasa kwa kuwa umechunguza dhana na mawazo muhimu, ni wakati wa kuweka ujuzi wako kwa mtihani. Sehemu hii inatoa mazoezi mbalimbali maswali yaliyoundwa ili kuimarisha uelewaji wako na kukusaidia kupima ufahamu wako wa nyenzo.

Utakutana na mchanganyiko wa aina mbalimbali za maswali, ikiwemo maswali ya kuchagua jibu sahihi, maswali ya majibu mafupi, na maswali ya insha. Kila swali limebuniwa kwa umakini ili kupima vipengele tofauti vya maarifa yako na ujuzi wa kufikiri kwa makini.

Tumia sehemu hii ya tathmini kama fursa ya kuimarisha uelewa wako wa mada na kubaini maeneo yoyote ambapo unaweza kuhitaji kusoma zaidi. Usikatishwe tamaa na changamoto zozote utakazokutana nazo; badala yake, zitazame kama fursa za kukua na kuboresha.

  1. What is data compression? A. Encoding data so it uses fewer bits while representing the same information B. Deleting parts of a file that are not needed C. Converting a file from binary into hexadecimal D. Copying a file to a second storage device Answer: A
  2. Using run length encoding with frequency first, how is the binary data 00011000 represented? A. 3 0 2 1 3 0 B. 0 3 1 2 0 3 C. 3 2 3 D. 8 0 Answer: A
  3. Why does run length encoding work poorly on a file of English text? A. Text files are always too large to compress B. Consecutive characters are usually different, so runs are very short C. Text is stored in Unicode rather than in binary D. Run length encoding can only be used on numbers Answer: B
  4. In a Huffman tree, which characters end up with the shortest codes? A. The ones that occur least often B. The ones that occur most often C. The ones that come first alphabetically D. All characters get codes of equal length Answer: B
  5. A message of 20 characters is stored in 7-bit ASCII. How many bits does it need uncompressed? A. 27 B. 60 C. 140 D. 160 Answer: C

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