Write algorithms using pseudocode or flowcharts

Resources | Subject Notes | Computer Science

IGCSE Computer Science - Algorithm Design and Problem Solving

Algorithm Design and Problem-Solving

This section focuses on developing and representing algorithms to solve computational problems. We will explore using pseudo-code and flowcharts to design step-by-step instructions for a computer to follow.

Pseudo-code

Pseudo-code is an informal way of describing an algorithm. It uses a combination of natural language and structured keywords to outline the steps involved. It's not a programming language but a blueprint for a program.

Common Pseudo-code Keywords

  • START / BEGIN: Marks the beginning of the algorithm.
  • INPUT: Indicates that data is being read from the user or a source.
  • OUTPUT: Indicates that data is being displayed to the user or sent to a destination.
  • IF ... THEN ... ELSE: Used for conditional execution.
  • WHILE ... DO ... ENDWHILE: Used for repetitive execution based on a condition.
  • FOR ... DO ... ENDFOR: Used for repetitive execution a fixed number of times.
  • RETURN: Indicates the end of a procedure and the value to be returned.

Example: Calculating the area of a rectangle

Suggested diagram: A rectangle with width 'w' and height 'h' labeled.

        START
        INPUT width, height
        OUTPUT area
        area = width * height
        END
        

Flowcharts

Flowcharts are diagrams that visually represent an algorithm. They use standard symbols to show the flow of control and the steps involved.

Common Flowchart Symbols

Symbol Name
Process/Operation
Decision
Input/Output
Connector

Example: Calculating the area of a rectangle (Flowchart)

Suggested diagram: A flowchart showing the steps to calculate the area of a rectangle, including input, calculation, and output.

        START
        INPUT width, height
        Process: area = width * height
        OUTPUT area
        END
        

Algorithm Design Strategies

Several strategies can be used to design effective algorithms:

  1. Decomposition: Breaking down a complex problem into smaller, more manageable sub-problems.
  2. Abstraction: Focusing on essential details and ignoring irrelevant information.
  3. Pattern Recognition: Identifying common algorithmic patterns and adapting them to new problems.

Example Problem: Finding the largest number in a list

Let's design an algorithm to find the largest number in a list of numbers.

Pseudo-code

    START
    INPUT list of numbers
    SET largest = first number in list
    FOR each number in list
        IF number > largest THEN
            SET largest = number
        ENDIF
    ENDFOR
    OUTPUT largest
    END
    

Flowchart

Suggested diagram: A flowchart illustrating the steps to find the largest number in a list.

This example demonstrates how to translate a problem into a structured algorithm using both pseudo-code and a flowchart. Understanding these techniques is crucial for problem-solving in computer science.