Unit 10 Computational Thinking

Unit 10 Computational Thinking

1. Thinking Techniques

   • Thinking Abstractly
     • Removing details that are irrelevant to the problem making it possible to solve
     • An example of abstraction would be the public transport system
     • Data Structures
     • Needed to make complex problems solveable
   • Thinking Procedurally
     • Procedural decomposition means breaking a problem into sub-problems that accomplish a task.
   • Thinking Logically
   • Thinking Concurrently
   • Thinking Ahead
     • Planning sections of code to ensure that it does not produce errors or unexpected behaviour
     • Input List of Integers: Output: largest number in the list Prerequisites: The list is not empty
     • Needed to make programs that are dependent on others work together without errors
     • Caching
       • Storing data that is frequently used so there is faster access
       • Webpages having data stored on a client computer

2. Computational Methods

   • Backtracking
   • Data Mining
   • Heuristics
     • Finding a solution to a problem that is not optimal but it can be computed quickly
     • Path finding algorithms like A*
     • Find a car - thinking about the optimal car features you want and settling with one that has the most, saving time searching for it
   • Performance Modelling
   • Pipelining
   • Visualisation
   • Problem Recognition