2.1 Algorithms

2.1 Algorithms

1. Decomposition

   • Breaking down large tasks into smaller, more manageable tasks.
   • Decomposition can involve different types of sorting.
   • There are many types of sorting the data for example.
     • Bubble Sorting.
     • Merge Sorting
     • Quick
     • Quick Sorting.
   • It takes less time to decompose the task and execute it than doing it all in one.

2. Abstraction

   • Removing the irrelevant details and it translates it into real world worlds.
   • This task can similar sorting methods.
   • An example of this is using icons to represent people on a map in a game.
     • This removes the need to have big icons for players and makes it more efficient.

3. Algorithms

   • A set of instructions to follow to complete a task
   • We face many of these algorithms every day but through the skills of:
     • Abstraction, Pattern Recognition, Decomposition and computational thinking. It narrows down the task so we can manage it.
   • The computer uses algorithms for "Trouble Shooting".
     • The computer analyzes what is wrong and uses smaller steps (decomposition) to diagnose it.

4. Computational Thinking

   • Using a computer mind set to solve problems.
   • In WW2 the Enigma device was used to crack enemy's codes
   • This was one of the reasons we managed to win the war.

5. Searching

   • Linear
     • A long winded method of searching for a result.
       • It involves going through every piece of data.
       • Worst Case Scenario:
         • It will go through every piece of data.
       • Best Case Scenario:
         • It only goes through 1-2 pieces of data.
   • Binary
     • This involves splitting the maximum number of values by 2.
     • Must be in order.
     • It checks if the number is greater than, equal to, or less than the valued number.
     • It is quicker than Linear searching however it is more complex to code.