2. What is computational
thinking ?
Decomposition
The break down How it helps
Pattern recognition Abstraction
Algorithms Evaluation
Summary
3. What is computational thinking ?
• Computational thinking is the process that involves formulating a
problem and expressing the solution, in the way that the computer can
carry out.
• The process are
• decomposition
abstraction
• Pattern recognition
• algorithms
•
4. Decomposition
• Decomposition is the breaking down of a complex problem into smaller
parts that are more understandable and easier to manage. These smaller parts
can be solved or designed individually .
• Decomposition is important due to the fact that, when a problem is in
different stages a problem can be solved quicker.
• Decomposition-The breaking down of a system into smaller parts that are
easier to understand, program and maintain.
5. The break down
• During our daily life we break down problems so that we can do it efficiently and for it to be easy to understand. Such as
making toast –
• Slice of bread, Plate, Small amount of butter, Toaster, Get a slice of bread
• Plug in the toaster and switch it on
• Place bread in the toaster
• Push the lever to lower the toast
• Wait a few minutes for the toast to pop up out of the toaster
• Take the toast out of the machine being careful not to burn your hands
• Place the toast on a plate
• Spread a little bit of the butter on the toast using a knife
• Cut the toast in half using the knife
6. How it helps
• If you are writing a long list of repeated code, decomposition helps you to
copy that text and repeat it.
• It is a very useful technique that help decompose complex problems.
•It help organise !
7. Pattern recognition
• In Computational thinking, these characteristics are known as
patterns. Once we know how to describe one cat we can describe
others, simply by following this pattern. The only things that are
different are the specifics
• E.g. colour of eyes, hair colour facial tone…
8. Abstraction
• Abstraction is the process of filtering out – ignoring - the
characteristics of patterns that we don't need in order to
concentrate on those that we do. It is also the filtering out
of specific details. From this we create a representation
of what we are trying to solve.
9. Algorithms
• In an algorithm, each instruction is identified and the order in
which they should be carried out is planned. Algorithms are often
used as a starting point for creating a computer program, and they
are sometimes written as a flowchart or in pseudocode.
• To tell it to do something you need steps and to do this you need
algorithms.
10. Evaluation
• Evaluation is the checking that a software is compatible for what its made
for.
• This is essential as it makes the program usable and fluent.
11. Summary
• 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 (egg as quickly as possible/using least space)?
• meets any design criteria we have been given
13. What is Robust
Programming ?
Purpose of Testing
Runtime Errors
Syntax Errors
Logic Errors
Types of Testing
Selecting and
using Suitable
Test
Test Plans
Key Words
Plenary
29. Input Validation
• This is a check made by a computer to ensure that the data entered is
sensible or reasonable.
• It attempts to ensure that it is within a certain limits and rules.
• E.G,
