2.1 Algorithms

2.1 Algorithms

1. Computational thinking

   • Pattern Recognition
     • Similar or repetitive instructions
       • • 3
       • • 1
       • 2
   • Abstraction
     • Examine a problem and identify its most essential details
       • • The top image shows a map of London, including the roads, tube stations, parks, river etc. This is brilliant if you are wanting to walk or drive around London. However, if you want to use the Underground, it isn't much use as it has far too much detail and much of that detail is not needed. The second diagram shows a map of the London Underground. All of the unnecessary detail has been removed so that you can see just the information that you actually need. Removing all of the unnecessary detail is what is meant by 'abstraction'
   • Algorithmic thinking
     • A way of getting to a solution through the clear definition of the steps needed.
     • Rather than magically coming up with an answer you develop a programme.
   • Top Down Design
     • How you can describe the problems which can be split into smaller elements
   • Decomposition
     • When a problem is broken down into smaller, simpler tasks
       • • image source: http://www.bing.com/images/search?view=detailV2&ccid=RhRv5vQE&id=4B5B15613D71B5E7B1AC8C2271BE23A482DF66DA&thid=OIP.RhRv5vQEsrNn14o2SDBm-AHaEp&q=decomposition+computing&simid=608019890557812931&selectedIndex=11&adlt=strict&ajaxhist=0

2. Searching Algorithms

3. Sorting Algorithms

4. Pseudocode

5. Flow diagrams

6. Completing algorithms

Bilder und Dateien der Mindmap