2.1 Algorithms

2.1 Algorithms

1. Computational Thinking

   • A way of understanding problems so that a solution can be formed
     • Decomposition
       • Breaking down a problem into small parts
         • For example, breaking down brushing your teeth
     • Abstraction
       • removing details that aren't needed
         • For example, a map
     • Algorithmic thinking
       • identifying the steps to solve a problem

2. Pseudocode

   • a way to write algorithms using code like statements

3. Flow diagrams

   • Visually represent the steps for an algorithm
   • Terminator
     • Used at the start or end
   • Process
     • used represent a process
   • Input/Output
     • used if something is inputted or outputted
   • Decision
     • used to represent when a decision or selection is made

4. Search algorithm

   • instructions to find an item in a data set
   • Linear search
     • Compare first item to one you need to find
       • If they match stop
         • Move onto next item if they dont
           • repeat steps until it matches
     • Very easy but slow
   • Binary search
     • Very efficient but only works on sorted data
     • Find the middle item in the list
       • compare middle item to target
         • if target is smaller than item cut off larger half
           • if target is larger cut off smaller
             • repeat until target is found

5. Sorting algorithm

   • instructions to set data into an order
     • Bubble sort
       • Simple but slow
       • Compare first 2
         • smaller one goes first
           • do this with 2 and 3, 3 and 4 etc
     • Merge sort
       • very efficient but slower than insertion sorts
         • split list in half then half until each number is separate while doing this compare values
     • insertion sort
       • Simple but doesn't cope well with long lists
       • if the items selected before are bigger than the new one selected it will go in front of them