2.2.2 - computational methods

Question 1

divide and conquer

Answer 1

1- Take a problem or data set
2- Apply some rules
3- Based on the outcome of these rules, discard any data that doesn’t match
4- Repeat process with remaining data

Question 2

3 examples of divide and conquer

Answer 2

1- binary search
2- merge sort
3- quick sort

Question 3

backtracking

Answer 3

The process of incrementally building towards a solution, abandoning partial success when the solution can’t be completed and going back to a previously successful match.

Question 4

3 examples of backtracking

Answer 4

1- path finding
2- depth first traversal
3- sudoku

Question 5

data mining

Answer 5

The concept of analysing vast amounts of data gathered from a variety of sources to discover new information and trends.

Question 6

heuristics

Answer 6

An approach to solving problems that allows us to use our experience and find a solution that has a high probability of being correct and can be considered ‘good enough’.

Question 7

performance modelling

Answer 7

Uses simulations and mathematical approximations before implementing situations in the real world, without having to perform detailed testing, which may be prohibitive in terms of time and costs.

Question 8

pipelining as a computational method

Answer 8

Splitting a large task into manageable chunks and overlapping these smaller processes to speed up the overall process.

Question 9

3 examples of pipelining

Answer 9

1- instruction pipelining
2- software pipelining
3- graphics pipelining

Question 10

visualisation as a computational method

Answer 10

Computer scientists make use of graphical representations of data in order to find solutions.