Evaluating solutions
Before solutions can be programmed, it is important to make sure that it properly satisfies the problem, and that it does so efficiently. This is done through evaluation.
What is evaluation?
- is easily understood – is it fully decomposed?
- is complete – does it solve every aspect of the problem?
- is efficient – does it solve the problem, making best use of the available resources (eg as quickly as possible/using least space)?
- meets any design criteria we have been given
If an algorithm meets these four criteria it is likely to work well. The algorithm can then be programmed.
Failure to evaluate can make it difficult to write a program. Evaluation helps to make sure that as few difficulties as possible are faced when programming the solution.
Why do we need to evaluate our solutions?
What happens if we don’t evaluate our solutions?
Once a solution has been decided and the algorithm designed, it can be tempting to miss out the evaluating stage and to start programming immediately. However, without evaluation any faults in the algorithm will not be picked up, and the program may not correctly solve the problem, or may not solve it in the best way.
Faults may be minor and not very important. For example, if a solution to the question ‘how to draw a cat?’ was created and this had faults, all that would be wrong is that the cat drawn might not look like a cat. However, faults can have huge – and terrible – effects, eg if the solution for an aeroplane autopilot had faults.
Ways that solutions can be faulty
We may find that solutions fail because:
- it is not fully understood – we may not have properly decomposed the problem
- it is incomplete – some parts of the problem may have been left out accidentally
- it is inefficient – it may be too complicated or too long
- it does not meet the original design criteria – so it is not fit for purpose
A faulty solution may include one or more of these errors.
