2.1 Algorithms

2.1 Algorithms

1. Computational thinking

   • Abstraction
     • A computational thinking technique that removes unnecessary detail to focus on relevant parts of the problem
   • Computational thinking is a way of understanding complex problems in order to form a solution that can be implemented by either a computer, a human or of both.
   • Decomposition
     • Decomposition means breaking down a complex problem into smaller parts.
     • Each part can be solved individually
   • Algorithm building blocks
     • Iteration - steps that repeat, either for a fixed number of times or until a condition is met.
     • Sequence-a sequence of steps completed one at a time
     • Selection-steps that only occur when conditons that are required are met
   • Computational Thinking is all about applying techniques from the world of Computer Science to solve problems, either in computing or in real life.

2. Pseudocode and flow charts

   • Pseudocode is a way of writing an algorithm with code like statements
   • Not a real programming language
   • Flow charts
     • Flow diagrams visually represent the steps that make an algorithm.
     • The arrows in a flow diagram represent the flow of control through the algorithm.

3. Searching algorithms

   • A search algorithm is a set of instructions for finding a specific item of data within a data set.
   • Linear search
     • Moves acroos the list one by one until it lands on the targeted value
   • Binary search
     • Binary search is a very efficient search algorithm but only works on sorted data.
     • Binary search works by comparing the middle item in the dataset to the target and "cutting off" half the dataset each time.
     • E.G if there was 100 numbers it would go to 50 and determine whether it is lower or higher