Introduction to Algorithmic Constructs

Algorithms form the foundation of all computer programs. To create efficient, structured, and effective algorithms, computer scientists rely on three fundamental constructs: sequencing, selection, and iteration. These constructs allow computers to process information, make decisions, and repeat actions efficiently.

Understanding these constructs is essential for solving problems using computational thinking. Without them, writing functional and logical programs would be impossible.

1. Sequencing: The Order of Execution

What is Sequencing?

Sequencing refers to the specific order in which instructions are executed in an algorithm. Each step must be performed in the correct sequence for the algorithm to produce the expected outcome.

Real-Life Example of Sequencing:
Consider a simple task like making a sandwich:

1. Take two slices of bread.
2. Spread butter on one slice.
3. Add a layer of peanut butter or jam.
4. Place the second slice on top.
5. Cut the sandwich in half and serve.

If the steps are performed in the wrong order (e.g., placing the second slice before spreading butter or jam), the outcome would not be the intended sandwich.

Sequencing in Computer Science

In programming, sequencing ensures that instructions execute one after another in the correct order.

Example in Pseudocode:

START

DISPLAY “Enter your name”

INPUT name

DISPLAY “Hello, ” + name

END

Here, the sequence ensures that the user first enters their name before the program greets them. If the steps were reversed, the program would not work correctly.

Sequencing in Flowcharts:

A flowchart is a visual representation of an algorithm. In a flowchart, sequencing is represented by a top-down flow of actions.

Example Flowchart for Making Tea:

1. Start
2. Boil water
3. Add tea leaves
4. Pour water into a cup
5. Add sugar/milk (optional)
6. Stir and serve
7. End

A flowchart ensures each step occurs in the correct order to achieve the intended result.

2. Selection: Decision-Making in Algorithms

What is Selection?

Selection (also called decision-making) allows an algorithm to choose between different paths based on a condition. It is commonly implemented using if-else statements.

Real-Life Example of Selection:

Imagine you want to decide what to wear based on the weather:

• IF it is raining, THEN take an umbrella.
• ELSE wear sunglasses.

This simple decision-making process helps us make logical choices depending on conditions.

Selection in Computer Science

Selection statements allow programs to react dynamically to input.

Example in Pseudocode:

START

INPUT temperature

IF temperature > 30 THEN

    DISPLAY “It is hot outside.”

ELSE

    DISPLAY “The weather is cool.”

END

If the user inputs 35, the output will be “It is hot outside.” If the input is 25, the output will be “The weather is cool.”

Selection in Flowcharts

Decision-making is represented in flowcharts using diamond-shaped decision boxes.

Example:

• Start
• Input the temperature
• Is temperature > 30°C?
  • Yes → Display “It is hot outside.”
  • No → Display “The weather is cool.”
• End

Selection is crucial for creating interactive programs, as it enables decision-making based on conditions.

3. Iteration: Repeating Instructions (Loops)

What is Iteration?

Iteration, or looping, allows an algorithm to repeat a set of instructions until a condition is met. This makes programs efficient, reducing repetition in code.

Real-Life Example of Iteration:

Think of brushing your teeth. You don’t just brush once; you repeat the motion multiple times to clean your teeth properly.

Example:

1. Pick up the toothbrush.
2. Apply toothpaste.
3. Repeat brushing motion 30 times.
4. Rinse and finish.

The brushing motion is repeated multiple times to ensure effective cleaning.

Iteration in Computer Science

There are two main types of loops:

1. Count-Controlled Loops (Fixed Repetition) – The loop runs a specific number of times.
2. Condition-Controlled Loops (Variable Repetition) – The loop runs until a condition is met.

Example of a Count-Controlled Loop (For Loop in Pseudocode):

START

FOR x = 1 TO 5

    DISPLAY “Hello”

END FOR

END

Output:

Hello  

Hello  

Hello  

Hello  

Hello  

The loop executes exactly 5 times.

Example of a Condition-Controlled Loop (While Loop in Pseudocode):

START

x = 1

WHILE x ≤ 5 DO

    DISPLAY “Hello”

    x = x + 1

END WHILE

END

This loop runs until the condition (x ≤ 5) becomes false.

Iteration in Flowcharts

A loop in a flowchart contains a decision box that checks whether to repeat the process.

Example: Counting from 1 to 5:

• Start
• Set x = 1
• Is x ≤ 5?
  • Yes → Display “Hello”, Increase x by 1
  • No → End

Why These Constructs Matter

All algorithms are built using these three fundamental constructs. Whether solving real-world problems or designing software, sequencing, selection, and iteration are essential in structuring logical solutions.

Summary of Algorithmic Constructs:

Looking Ahead

Now that we have learned the fundamental building blocks of algorithms, the next step is to trace and analyze algorithms step by step (covered in Chapter 7.3). This will help in identifying logic errors and understanding how algorithms execute before implementing them in programming.