2.1 computational thinking

Question 1

computational thinking

Answer 1

think logically and apply techniques to solving
the problem should be solvable with an algorithm

Question 2

definition of abstraction

Answer 2

taking away the unnecessaries to focus on essence of a problem //separation of physical and logical aspects of problem

reduce computational resources

Question 3

need for abstraction

Answer 3

problems need to be formulated for computers to solve

Question 4

examples of abstraction

Answer 4

queuing
London underground maps
google map

Question 5

procedural decomposition

Answer 5

breaking problems into number of subproblems
for identifiable tasks

Question 6

definition of structured program

Answer 6

it aims to improve clarity and quality of program, as well as maintainability

Question 7

input, output , preconditions

Answer 7

input:information relevant to the problem

output:solution to the problem

preconditions: e.g. there must be a base case, list must not be empty

Question 8

use of input, output and preconditions

Answer 8

writing bug-free, reusable program components

Question 9

definition of caching

Answer 9

temporary storage of data and instructions
e.g. web caching: storing html pages recently looked at

Question 10

benefits of caching

Answer 10

-faster access to resource
-saving bandwidth
-reduce load in a client-server environment

Question 11

drawback of caching

Answer 11

-slower performance if the resource could not be found from cache
-copy of resource not up to date

Question 12

definition of good algorithm

Answer 12

clear steps , correct output
allow invalid inputs
must terminate
execute efficiently( few steps as possible)
able to be understand or modified by others