### Digital Analysis, Legislation & Emerging Issues

Content Area 1: Problem Solving
Computational Thinking
Algorithms
Content Area 2: Introduction to Programming
Program Data
Operators
File Handling
Program Structure
Built-In Functions
Standard Algorithms
Validation & Error Handling
Maintainable Code
Testing
Content Area 3: Emerging Issues & Impact of Digital
Moral & Ethical Issues
Content Area 4: Legislation & Regulatory Requirements
Legislation
Guidelines & Codes of Conduct

# Modularisation & Decomposition

Whenever a computer programmer sits down to write a program, they are faced with the same problem every single time: what is the program going to do and how is the programmer going to build it?

There are several approaches to problem-solving, including tackling the problem from the bottom, or the top, or breaking the problem into functionally distinct areas.

In this lesson we will learn about:

1. Using a top-down and bottom-up approach to problem-solving
2. Using a modularisation approach to problem-solving
3. Identifying and describing the main features of problems and processes
4. Breaking down problems and processes into distinct steps

## 1. Using a Top-Down & Bottom-Up approach

Imagine you have been asked to cook dinner.

The first step is to find out as much information as you can about what you are being asked to do. For example:

• How many people are you cooking for? This will determine how much food to buy.
• Do any of your guests have allergies? This will determine what kind of food you should buy.
• What kind of equipment do you have in your kitchen? This will determine how you can cook the food.

In programming, identifying the problem means getting used to the PROBLEM DOMAIN – the area where your program will end up being used.

If you are writing a program to help chemical engineers visualise proteins in the body, you will need to understand the technical terminology required by end-users.

A top-down approach is where you look at the problem as a whole and then start to break it down into smaller problems.

For example, you decide to break up the dinner into a starter, main and pudding courses.

A bottom-up approach is where you identify a list of small tasks that you already know about, and then you assemble them together into a larger task.

For example, you know you’ll need some pans of boiling water, you’ll need the oven turned on, and you’ll need some vegetables peeled.

You then start to assemble these together to create your dinner.

An example of top-down and bottom-up approaches is shown in Figure 1.1.

### Further Thought

Imagine you are given an unfamiliar problem. Is top-down or bottom-up a better approach?

## 2. Using a Modularisation Approach

A module is where processes that have things in common are grouped together. The group is called a Module. This could be a Code Object or a Library of Functions.

For example – you might have a module that contains all the functionality you need to read and write from files.

If you were to modularise the dinner, you would identify an ‘Oven’ module. This would have functions to set the temperature and the timer.

You would then work out which of your meal ingredients need to use the oven and which oven functions are needed.

One module can use the functions of another. For example, roasting meat would use the Oven functions.

An example of a modular approach to preparing dinner is shown in Figure 1.2.

### Further Thought

Can you think of any disadvantages of a modular approach to problem-solving?

## 3. Identifying & Describing the Main Features

When looking at your dinner problem, you will need to work out how you are going to go about solving the problem.

The first thing you would need to do is identify the main features of the problem. In this example, you decide to break the task down into a Starter, Main and Pudding.

This process of taking a larger problem and breaking it down into smaller, more manageable problems is called Decomposition.

The first step of decomposition is working out what the main features of a given problem are which is shown in figure 1.3.

### Further Thought

Which computational problem-solving approach does decomposition remind you of?

## 4. Breaking a Problem Down

You need to keep decomposing the problem until you arrive at a series of steps that cannot be broken down any further.

You should be able to put all the individual steps back together to make a complete program.

In the example shown in Figure 1.3, the process ‘make other vegetables’ could be broken down into further steps. For example:

When you have broken the problem down into a set of clear, easy-to-follow steps, your problem is Fully Decomposed.

At this stage, you can hand the problem over to a programmer, and they should be able to follow your steps.

For a real-world example, every password-based login process must follow these steps.

1. Check the password entered by the user against the password stored in the system.
2. If the password matches, the user is logged in.
3. If not, an error message is displayed.

Entering the username and password would need code from the user interface module.

Sending data to the database would need code from the database module.

Figure 1.4 shows the decomposition of this process using modularisation.

### Further Thought

Can a fully decomposed problem be solved by a Bottom-Up approach?

## Lesson Summary

So, to summarise what we have learned in this lesson:

• The problem domain is the field where your program will be used.
• A top-down approach is where a large problem is broken down into smaller problems.
• A bottom-up approach is where a series of smaller tasks are put together to solve a problem.
• Modularisation is where related sets of functionalities are grouped together.
• Decomposition of a problem involves identifying the main features of a problem.
• Decomposition then involves breaking a problem down into smaller tasks.
• Once each task cannot be broken down any further, the problem is fully decomposed.
Quizzes