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2.1 Algorithms

2402 2003 Computing GCSE English

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2.1 Algorithms

  1. Computational Thinking

    • Allows us to take a complex problem, understand what the problem is, and then develop possible solutions
    • The use of a computer to solve problems
    • 4 Key Areas:
      • Decomposition
        • Breaking down a complex problem or system into smaller, more manageable parts
      • Abstraction
        • Gets rid of the irrelevant stuff in the program
        • Allows to only focus on the important information
      • Pattern Recognition
        • Looking for similarities among and within problems
      • Algorithms
        • Developing a step-by-step solution to solve the problem
        • Algorithms must be detailed & easy to understand so it can be passed onto someone else and have them code it
  2. Binary Search

    • List must be in order
    • Middle Value is taken
      • Search is stopped if it is the value is the one you're looking for
      • If middle value is larger than the desired one: Take the values to the left of the middle value
        • Then repeat with the new list
      • If middle value is smaller than the desired one: Take the values to the right of the middle value
  3. LInear Search

    • List does not have to be in order
    • First value of list is checked
      • Search is stopped if it is the value is the one you're looking for
      • If not desired value: Check next value on the list
        • Process is repeated until desired value is attained
  4. Bubble Sort

    • A method for sorting out unordered lists
    • Take the first and second elements from the list and compare them
      • If element 1 > element 2: Swap
        • Else: Leave it
          • Move along to the next pair of elements (element 2 & 3) and repeat
            • Repeat until you have moved through the whole list and not made any changes
    • Worst case scenario: n*n (n = number of elements) Average number of swaps: n^2
  5. Merge Sort

    • A list is split into individual lists, these are then combined (2 lists at a time)
    • Split all elements into individual lists
      • Compare the first element into first two lists
        • Put the smallest at the start of a new list
          • Compare the next element of the 1st list with the next element of the 2nd list
            • Put the smallest into a new list
              • Repeat until first two lists merged
                • Then repeat with other lists
            • If you have two values the same, add one (it doesn't matter from which list), and then add the second
  6. Insertion Sort

    • Comparing unsorted elements in an individual list and sorting then out in order
      • In a list, the starting element is a 'sorted' list
        • The rest of the elements are an 'unsorted' list
          • Compare the first element in the 'unsorted' list with all the elements in the 'sorted' list
            • If the current unsorted element is smaller than the interacted sorted element, put it in front of that element (move the other sorted elements along)
            • If the unsorted element is larger, compare it with the next
            • If there are no more elements in the 'sorted' list, put it in the final position
              • Repeat until all elements in the 'unsorted' list are in the 'sorted' list
  7. Flow Chart

    • Can be used to represent an algorithm
    • It shows the data that is inputted and outputted
      • It shows the processes (actions) that take place
        • It shows the decisions and repetitions that take place
          • Lines are used to show the flow of control
            • Set shapes are used to represent different functions
              • Diamond - Decision
              • Oval - Start/End
              • Rectangle - Process
              • Parallelogram - Input/Output
              • Rectangle with 2 interior lines - Sub-Process
  8. Pseudocode

    • 'Fake code'
    • Part way between English sentences, and programming code
    • It is language neutral (it can be read by programmers who are able to use any language)
    • Dry Run - Walking through an algorithm which sample data, running each step manually
    • Trace Table - A table that follows the values of variables to check for accuracy

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GCSE Computing (2.1 Algorithms) Mind Map on 2.1 Algorithms, created by 2402 2003 on 17/12/2018.
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2402 2003
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