2.1 Algorithms

2.1 Algorithms

computational thinking
1. Abstraction
  1. getting rid of irrelevant information and focusing on important information
  2. using symbols and variables to represent "real world" problems
2. decomposition
  1. big problem ==> smaller problems
    1. easier to solve
    2. independent of others
  2. problems can be decomposed in different methods
3. Algorithmic thinking
  1. identifying steps in solving problems
linear search
1. doesn't need to be in order
2. goes through one by one
3. IF correct, stop
4. ELSE carry on to next value
5. simpler to write
binary search
1. list needs to be in order
2. take middle value
3. compare to required value
4. IF correct then stop
5. ELSEIF it is larger, take values on the left
6. IF smaller, take values to the right
7. longer, more complex
sorts
1. bubble
  1. goes through list repeatedly swapping elements until in correct order
2. merge
  1. list is split in two and combined two at a time
3. insertion
  1. each item is taken in turn compared to an ordered list. it is placed in correct position
flowchart
1. input / output data
2. processes
3. decisions
4. shapes rep functions
5. lines show flow control
pseudocode
1. 'fake' code
2. partway between sentences and coding
dry run
1. walking through and running each step manually
2. trace table
  1. table that follows the values of variables to check for accuracy

Resource summary

	Created by Jack Rowley over 5 years ago