Algorithms

• Computation Thinking

  • Decomposition: breaking a complex problem down into smaller problems and solving each one individually.
  • Algorithmic Thinking: A logical way from the problem to the solution. If the steps you take to solve a problem follow an algorithm, they can be used for similar problems in the future.
  • Abstraction: Picking out important bits from the information, ignoring what doesn't matter.
• Algorithmic Thinking: A logical way from the problem to the solution. If the steps you take to solve a problem follow an algorithm, they can be used for similar problems in the future.
• Abstraction: Picking out important bits from the information, ignoring what doesn't matter.
• • Decomposition: breaking a complex problem down into smaller problems and solving each one individually.
• Pseudocode

  • Not an actual programming language, follows a similar structure.
  • Shows algorithm ignoring syntax so it can be used in any programming language.
  • Quick to write.
  • Easily converted.
• Terminals


  The beginning and the end of the algorithm.

  
• Parallelogram Box

  Anything that's taken into and out of the algorithm.

  
• Rectangular Box


  General processes, instructions, and calculations.

  
• Diamond Boxes


  Often 'yes' or 'no' questions.

  
• Arrows


  Connect boxes and show the direction that should be followed.

  
• What is computational thinking?

  It is the steps taken to find the best solution to a complex problem.
• What is decomposition in computational thinking?

  Breaking a complex problem down into smaller problems.
• What does abstraction involve in computational thinking?

  Picking out important information while ignoring irrelevant details.
• What is algorithmic thinking?

  A logical way of getting from the problem to the solution.
• How can computational thinking be applied in real life?

  By breaking down decisions into manageable tasks.
• What is the first step in algorithmic thinking when deciding which film to watch?

  Listing all the films that are showing.
• How does decomposition help in sorting product names alphabetically?

  It helps define what alphabetical order means and how to compare entries.
• What is the purpose of pseudocode in writing algorithms?

  Pseudocode shows an algorithm's steps without worrying about syntax.
• What is an example of a simple pseudocode algorithm?

  Take worker’s current salary, multiply by 1.1, display the answer.
• Why should pseudocode not be too vague?

  It needs to be readable and easy to interpret.
• What do flow diagrams use to represent different commands?

  Different shapes for different commands.
• What does a diamond box represent in a flow diagram?

  A decision point, often a yes or no question.
• What is the purpose of arrows in flow diagrams?

  To show the direction of the flow of the algorithm.
• What is a binary search algorithm used for?

  To find items in an ordered list.
• What is the first step in a binary search algorithm?

  Find the middle item in the ordered list.
• What happens if the middle item in a binary search is not the target item?

  You compare the target item to the middle item and eliminate half the list.
• How does a linear search operate?

  It checks each item in the list one by one.
• What is the main difference between binary search and linear search?

  Binary search is for ordered lists, while linear search can be used on unordered lists.
• What is the first step in the binary search algorithm?

  Compare the item you're looking for to the middle item.
• What happens if the item you're looking for comes before the middle item in a binary search?

  You get rid of the second half of the list.
• How do you reduce the size of the list in a binary search?

  By eliminating half of the list based on the comparison with the middle item.
• How does the binary search algorithm improve efficiency compared to a linear search?

  It reduces the list size by half with each comparison.
• What is the main characteristic of a linear search?

  It checks each item in the list in turn.
• When does a linear search stop?

  When it finds the item or has checked every item.
• Why is a linear search often only used on small lists?

  Because it is inefficient for larger lists.
• What is the worst-case scenario for a linear search?

  Checking every item in the list without finding the target.
• What is the first step in the bubble sort algorithm?

  Look at the first two items in the list.
• What do you do if the first two items in a bubble sort are in the wrong order?

  Swap them.
• How do you know when to stop making passes in a bubble sort?

  When there are no swaps in a pass.
• What is a key advantage of the bubble sort algorithm?

  It can efficiently check if a list is already in order.