1. Topic 1: Problem Solving
Abstraction

2. Problem Solving: Abstraction
When it comes to creating a solution for a problem, there may be times when there is too much information
Data that isn’t needed for the solution
Stripping away (or hiding) this information is known as abstraction
Keeping only the key details/pieces of information needed to solve the problem
There are multiple types of abstraction, that deal with removing different details
Making the problem simpler to understand
Making the solution easier to understand
Problem Solving: Abstraction

3. Abstracting the Problem
This type of abstraction involves removing unnecessary information from the problem itself
For example, if the problem involves calculating the number of computers needed in a lab, we may not need to know
The tutor’s name
The types of computer
What programs the computers will be running
If this information is included in the problem, we can hide it and only focus on the bits we need
Problem Solving: Abstraction

4. Abstracting the Problem
For example, take this problem:
Casey is playing a game with her students in school. She has six boxes in front of her, each for a subject (Maths, Biology, Physics, Chemistry, Geography, and History). She asks one of her students to roll a die, and depending on the number picks a random question from one of the boxes (1  Maths, 2  Biology, 3  Physics, 4  Chemistry, 5  Geography, 6  History) and then asks the student that rolled the die that question. If they get it right, they earn a point. If they don’t, any student can answer the question (and earn a point if they get it right). In either case, the next student rolls the die and repeats the same steps.
Problem Solving: Abstraction

5. Abstracting the Problem
We can ‘cross out’ any unnecessary information (leaving only what we need to solve this problem)
Casey is playing a game with her students in school. She has six boxes in front of her, each for a subject (Maths, Biology, Physics, Chemistry, Geography, and History). She asks one of her students to roll a die, and depending on the number picks a random question from one of the boxes (1  Maths, 2  Biology, 3  Physics, 4  Chemistry, 5  Geography, 6  History) and then asks the student that rolled the die that question. If they get it right, they earn a point. If they don’t, any student can answer the question (and earn a point if they get it right). In either case, the next student rolls the die and repeats the same steps.
Problem Solving: Abstraction

6. Abstracting the Problem
We can also use decomposition to abstract the problem
Here we can take the problem itself
And break it into steps
With sub-steps as needed
This then makes the problem easier to read
Making a solution easier to make
A student rolls a die
Picks a question (based off die roll)
Student asked that question
If they get it right, they get a point
Otherwise any other student can answer (and get the point)
Move on to next student
Repeat from point 1
Problem Solving: Abstraction

7. Problem Solving: Abstraction
See if you can reduce the following problem to a more abstract form
A student is working on creating a Checkers game. Once the game has the board set up, they need to repeat the user and the computer taking turns until one of them wins. Each turn, a player can move a piece diagonally. The game needs to consider crowning a piece if it reaches their opponents side, and letting pieces take other pieces (by jumping over them). A player wins when their opponent has no pieces left.
Problem Solving: Abstraction

8. Abstracting the Solution
The other form of abstraction comes into play when we have a solution, which comes into two places
Abstracting the solution itself
Abstracting the data in the solution
Abstracting the data means taking the data from the ‘real world’
And thinking about it in more general terms
Problem Solving: Abstraction

9. Abstracting the Solution
For example, we have a cat
Certain fur colour
Tail length
Eye colours
We don’t need to know the details
Only the general structure
Also an example of information hiding
Though more obvious on practice
Used in public, private, protected
Problem Solving: Abstraction

10. Abstracting the Solution
When it comes to abstracting the solution, we tend to do that during implementation
Can also prepare for it during the design of a solution
There are ‘sub-types’ of abstraction here, but they all affect the code we enter for the solution
These are
Procedural Abstraction
Functional Abstraction
Data Abstraction
Used in programming the solution (to make it easier to read)
Problem Solving: Abstraction

11. Abstracting the Solution
Procedural Abstraction involves breaking parts of a solution off into their own procedure
Takes the ‘complexity’ away from the actual solution
Means we don’t need to know how that part is done
Only that it works as intended
A very important part to any complex solution
The procedure we make ends up not caring about the data used
Only how it works
We supply the data when we run this procedure
Here register_user is the abstracted procedure
Problem Solving: Abstraction

12. Abstracting the Solution
Functional Abstraction works similarly
Involves functions instead of procedures
That means a value is expected after running the function
When designing/implementing, we still don’t care how this function works
As long as it does what we expect
Here length_between_points is the abstracted function
Problem Solving: Abstraction

13. Abstracting the Solution
Finally, Data Abstraction comes back to what we were talking about earlier
With the Cat
When thinking about data (especially in the design), we don’t care how we represent this data
For example, we need to represent ‘students’ in a program
What information do we need for a ‘Student’
How do we store multiple ‘Students’
The solution doesn’t care how we do this
It’s up for us to decide when programming
Problem Solving: Abstraction

14. Other Forms of Abstraction
There are other uses of abstraction as well
Not just related to problems and solutions
For example, high-level programming languages
They are abstractions of the more complex low- level languages
They make it easier to tell the computer to do something
When using high-level languages, we don’t care how the computer does something
We only tell it to do something
Problem Solving: Abstraction