Introduction to Algorithms

What is an Algorithm?

An algorithm is a step-by-step procedure to solve a problem or accomplish a task. It's like a recipe that tells you exactly what to do, in what order!

Before writing any code, programmers first think about the steps needed to solve a problem. These steps, when written down clearly, form an algorithm. An algorithm is the blueprint of your program.

01Algorithms in Daily Life

You use algorithms every day without realizing it! Here are some examples:

Making an Omelette

1. Take 2 eggs
2. Break eggs into a bowl
3. Add salt and pepper
4. Beat the mixture
5. Heat oil in pan
6. Pour mixture into pan
7. Cook until done
8. Serve on plate

Driving to School

1. Get in the car
2. Put on seatbelt
3. Start the engine
4. Drive to first intersection
5. Turn left
6. Continue straight for 2 km
7. Turn right at school
8. Park the car

Key Insight

An algorithm is simply a clear, ordered set of instructions that leads to a specific result. The same applies to computer programs!

02Characteristics of a Good Algorithm

Not every set of instructions is a good algorithm. A proper algorithm should have these characteristics:

Clear & Unambiguous

Each step must be precise and clear. No confusion about what to do.

Well-Defined Inputs

May have zero or more inputs that are clearly specified.

Well-Defined Outputs

Must produce at least one output or result.

Finite Steps

Must end after a finite number of steps. Cannot run forever!

Effective

Each step should be simple and doable.

Language Independent

Can be implemented in any programming language.

03Example: Algorithm to Add Two Numbers

Let's write an algorithm to add two numbers. First, we'll write it in plain English, then in code.

Algorithm Steps:

1START

2Declare variables: num1, num2, sum

3Read values for num1 and num2

4Calculate: sum = num1 + num2

5Display sum

6END

C Code:

add.c

1#include <stdio.h>
2
3int main() {
4    int num1, num2, sum;
5    
6    printf("Enter first number: ");
7    scanf("%d", &num1);
8    
9    printf("Enter second number: ");
10    scanf("%d", &num2);
11    
12    sum = num1 + num2;
13    
14    printf("Sum = %d", sum);
15    return 0;
16}

04Example: Find Largest of Three Numbers

This algorithm uses conditions to make decisions. Let's find the largest among three numbers.

Algorithm:

1START

2Read three numbers: A, B, C

3IF A > B AND A > C, THEN largest = A

4ELSE IF B > A AND B > C, THEN largest = B

5ELSE largest = C

6Display largest

7END

Test Your Algorithm!

Try with A=5, B=9, C=3. Following the algorithm: Is 5 > 9? No. Is 9 > 5 AND 9 > 3? Yes! So largest = 9. ✓

04bWays to Represent Algorithms

There are several ways to write down and communicate algorithms. Each method has its advantages depending on the situation and audience.

Natural Language

Written in plain English (or your native language). Easy to understand but can be ambiguous. Best for initial brainstorming and explaining to non-programmers.

Example: "Take the first number, add it to the second number, display the result."

Flowcharts

Visual diagrams using shapes and arrows. Great for showing flow and decisions. Universally understood. Perfect for complex branching logic.

See our Flowcharts tutorial for details!

Pseudocode

A mix of natural language and programming structure. More precise than English, easier than real code. The most common format in textbooks and interviews.

IF score >= 60 THEN
PRINT "Pass"
ELSE
PRINT "Fail"

# Structured English

Uses keywords like IF, THEN, ELSE, WHILE, FOR in English sentences. More formal than natural language, less technical than pseudocode.

Common in business analysis and requirements documents.

Which Format Should I Use?

For learning: start with natural language, then add pseudocode structure. For interviews: pseudocode is expected. For team communication: flowcharts work great. For documentation: use all three together for clarity.

04cWhy Algorithm Efficiency Matters

Not all algorithms that solve a problem are equally good. Some are faster, some use less memory. As you progress, you'll learn to analyze and choose efficient algorithms.

Example: Finding a Number in a List

Slow: Check Every Element

Look at each item one by one until you find it. For 1 million items, might need 1 million checks!

Time: O(n) — linear

Fast: Binary Search (sorted list)

Check the middle, eliminate half each time. For 1 million items, only ~20 checks needed!

Time: O(log n) — logarithmic

Don't worry about the O notation now — just know that algorithm choice can mean the difference between seconds and hours of runtime!

05Algorithm vs Program

What's the difference between an algorithm and a program? Let's compare:

Algorithm	Program
Written in plain English or pseudocode	Written in programming language (C, Python, etc.)
Language independent - can be converted to any language	Language specific - follows syntax rules
Blueprint / Design phase	Implementation / Building phase
Easy to understand by anyone	Requires programming knowledge
Cannot be executed directly	Can be compiled and run

Pro Tip: Always Algorithm First!

Before writing any code, always write your algorithm first. It helps you:
• Think clearly about the problem
• Avoid bugs and logical errors
• Make coding much easier

06Practice: Write Your Own Algorithm

Try writing algorithms for these problems. Remember: use plain English, be specific, and number your steps!

# Problem 1: Check Even or Odd

Write an algorithm to check if a number is even or odd.

Hint: Use modulus (%) - if number % 2 == 0, it's even

Problem 2: Calculate Area of Rectangle

Write an algorithm to find area given length and width.

Hint: Area = length × width

07Frequently Asked Questions

Q:What's the difference between an algorithm and a program?

A: An algorithm is the idea — the step-by-step logic in plain language. A program is the implementation — the algorithm written in a specific programming language. One algorithm can be implemented in many languages (C, Python, Java).

Q:Why should I write algorithms before coding?

A: It's easier to think about logic without worrying about syntax. You catch errors in planning, not debugging. It clarifies your thinking and makes coding faster. Many professional developers sketch algorithms before writing any code.

Q:How detailed should my algorithm be?

A: Detailed enough that someone else could follow it without guessing. Each step should be simple and unambiguous. If a step is complex, break it into sub-steps. The test: could a non-programmer follow it?

Q:Are there "best" algorithms?

A: Different algorithms have different trade-offs: speed, memory usage, simplicity. For sorting, QuickSort is generally fast but MergeSort is more predictable. "Best" depends on your specific needs. Algorithm analysis helps you choose.

Q:What is Big O notation and why should I care?

A: Big O describes how an algorithm's runtime grows with input size. O(n) means linear growth; O(n²) means quadratic. Knowing this helps you predict performance and choose the right algorithm. For 1000 items, O(n) is 1000 operations; O(n²) is 1,000,000!

Q:How do I test if my algorithm is correct?

A: Trace through your algorithm with simple examples by hand first. Test edge cases: empty input, one element, duplicates, negative numbers, already-sorted data. Compare output against known correct results. Write multiple test cases before writing code.

!Code Pitfalls: Common Mistakes & What to Watch For

Common Mistakes with Algorithms

Copied code can produce code but often misses crucial algorithmic thinking:

✗Wrong complexity: Beginners often pick O(n²) algorithms when O(n log n) exists, causing performance disasters on large data
✗Infinite loops: Beginners often forget termination conditions or creates loops that never end
✗Off-by-one errors: Beginners often miscount loop iterations, causing algorithms to miss first or last elements
✗Missing base cases: Recursive algorithms from Copied code often lack proper termination

Design Algorithms Yourself

Write the algorithm in plain English first. Verify it handles all cases. Then Copied code can help implement it — but you've already done the hard thinking. Understanding algorithms lets you spot mistakes immediately.

08Summary

What You Learned:

✓Algorithm = step-by-step procedure to solve a problem
✓Must be clear, finite, and effective
✓Should have defined inputs and outputs
✓Algorithm is the blueprint, program is the implementation
✓Always write algorithm first, then code

What is an Algorithm?

An algorithm is a step-by-step procedure to solve a problem or accomplish a task. It's like a recipe that tells you exactly what to do, in what order!

01Algorithms in Daily Life

You use algorithms every day without realizing it! Here are some examples:

Making an Omelette

1. Take 2 eggs
2. Break eggs into a bowl
3. Add salt and pepper
4. Beat the mixture
5. Heat oil in pan
6. Pour mixture into pan
7. Cook until done
8. Serve on plate

Driving to School

1. Get in the car
2. Put on seatbelt
3. Start the engine
4. Drive to first intersection
5. Turn left
6. Continue straight for 2 km
7. Turn right at school
8. Park the car

Key Insight

An algorithm is simply a clear, ordered set of instructions that leads to a specific result. The same applies to computer programs!

02Characteristics of a Good Algorithm

Not every set of instructions is a good algorithm. A proper algorithm should have these characteristics:

Clear & Unambiguous

Each step must be precise and clear. No confusion about what to do.

Well-Defined Inputs

May have zero or more inputs that are clearly specified.

Well-Defined Outputs

Must produce at least one output or result.

Finite Steps

Must end after a finite number of steps. Cannot run forever!

Effective

Each step should be simple and doable.

Language Independent

Can be implemented in any programming language.

03Example: Algorithm to Add Two Numbers

Let's write an algorithm to add two numbers. First, we'll write it in plain English, then in code.

Algorithm Steps:

1START

2Declare variables: num1, num2, sum

3Read values for num1 and num2

4Calculate: sum = num1 + num2

5Display sum

6END

C Code:

add.c

1#include <stdio.h>
2
3int main() {
4    int num1, num2, sum;
5    
6    printf("Enter first number: ");
7    scanf("%d", &num1);
8    
9    printf("Enter second number: ");
10    scanf("%d", &num2);
11    
12    sum = num1 + num2;
13    
14    printf("Sum = %d", sum);
15    return 0;
16}

04Example: Find Largest of Three Numbers

This algorithm uses conditions to make decisions. Let's find the largest among three numbers.

Algorithm:

1START

2Read three numbers: A, B, C

3IF A > B AND A > C, THEN largest = A

4ELSE IF B > A AND B > C, THEN largest = B

5ELSE largest = C

6Display largest

7END

Test Your Algorithm!

Try with A=5, B=9, C=3. Following the algorithm: Is 5 > 9? No. Is 9 > 5 AND 9 > 3? Yes! So largest = 9. ✓

04bWays to Represent Algorithms

There are several ways to write down and communicate algorithms. Each method has its advantages depending on the situation and audience.

Natural Language

Written in plain English (or your native language). Easy to understand but can be ambiguous. Best for initial brainstorming and explaining to non-programmers.

Example: "Take the first number, add it to the second number, display the result."

Flowcharts

Visual diagrams using shapes and arrows. Great for showing flow and decisions. Universally understood. Perfect for complex branching logic.

See our Flowcharts tutorial for details!

Pseudocode

A mix of natural language and programming structure. More precise than English, easier than real code. The most common format in textbooks and interviews.

IF score >= 60 THEN
PRINT "Pass"
ELSE
PRINT "Fail"

# Structured English

Uses keywords like IF, THEN, ELSE, WHILE, FOR in English sentences. More formal than natural language, less technical than pseudocode.

Common in business analysis and requirements documents.

Which Format Should I Use?

04cWhy Algorithm Efficiency Matters

Not all algorithms that solve a problem are equally good. Some are faster, some use less memory. As you progress, you'll learn to analyze and choose efficient algorithms.

Example: Finding a Number in a List

Slow: Check Every Element

Look at each item one by one until you find it. For 1 million items, might need 1 million checks!

Time: O(n) — linear

Fast: Binary Search (sorted list)

Check the middle, eliminate half each time. For 1 million items, only ~20 checks needed!

Time: O(log n) — logarithmic

Don't worry about the O notation now — just know that algorithm choice can mean the difference between seconds and hours of runtime!

05Algorithm vs Program

What's the difference between an algorithm and a program? Let's compare:

Algorithm	Program
Written in plain English or pseudocode	Written in programming language (C, Python, etc.)
Language independent - can be converted to any language	Language specific - follows syntax rules
Blueprint / Design phase	Implementation / Building phase
Easy to understand by anyone	Requires programming knowledge
Cannot be executed directly	Can be compiled and run

Pro Tip: Always Algorithm First!

Before writing any code, always write your algorithm first. It helps you:
• Think clearly about the problem
• Avoid bugs and logical errors
• Make coding much easier

06Practice: Write Your Own Algorithm

Try writing algorithms for these problems. Remember: use plain English, be specific, and number your steps!

# Problem 1: Check Even or Odd

Write an algorithm to check if a number is even or odd.

Hint: Use modulus (%) - if number % 2 == 0, it's even

Problem 2: Calculate Area of Rectangle

Write an algorithm to find area given length and width.

Hint: Area = length × width

07Frequently Asked Questions

Q:What's the difference between an algorithm and a program?

Q:Why should I write algorithms before coding?

Q:How detailed should my algorithm be?

Q:Are there "best" algorithms?

Q:What is Big O notation and why should I care?

Q:How do I test if my algorithm is correct?

!Code Pitfalls: Common Mistakes & What to Watch For

Common Mistakes with Algorithms

Copied code can produce code but often misses crucial algorithmic thinking:

✗Wrong complexity: Beginners often pick O(n²) algorithms when O(n log n) exists, causing performance disasters on large data
✗Infinite loops: Beginners often forget termination conditions or creates loops that never end
✗Off-by-one errors: Beginners often miscount loop iterations, causing algorithms to miss first or last elements
✗Missing base cases: Recursive algorithms from Copied code often lack proper termination

Design Algorithms Yourself

08Summary

What You Learned:

✓Algorithm = step-by-step procedure to solve a problem
✓Must be clear, finite, and effective
✓Should have defined inputs and outputs
✓Algorithm is the blueprint, program is the implementation
✓Always write algorithm first, then code

What You Will Learn

What is an Algorithm?

01Algorithms in Daily Life

Making an Omelette

Driving to School

Key Insight

02Characteristics of a Good Algorithm

Clear & Unambiguous

Well-Defined Inputs

Well-Defined Outputs

Finite Steps

Effective

Language Independent

03Example: Algorithm to Add Two Numbers

Algorithm Steps:

C Code:

04Example: Find Largest of Three Numbers

Algorithm:

Test Your Algorithm!

04bWays to Represent Algorithms

Natural Language

Flowcharts

Pseudocode

# Structured English

Which Format Should I Use?

04cWhy Algorithm Efficiency Matters

Example: Finding a Number in a List

Slow: Check Every Element

Fast: Binary Search (sorted list)

05Algorithm vs Program

Pro Tip: Always Algorithm First!

06Practice: Write Your Own Algorithm

# Problem 1: Check Even or Odd

Problem 2: Calculate Area of Rectangle

07Frequently Asked Questions

Q:What's the difference between an algorithm and a program?

Q:Why should I write algorithms before coding?

Q:How detailed should my algorithm be?

Q:Are there "best" algorithms?

Q:What is Big O notation and why should I care?

Q:How do I test if my algorithm is correct?

!Code Pitfalls: Common Mistakes & What to Watch For

Common Mistakes with Algorithms

Design Algorithms Yourself

08Summary

What You Learned:

Test Your Knowledge

Related Tutorials

What is Programming?

Understanding Flowcharts

Why Learn C? History of C

Have Feedback?

What You Will Learn

What is an Algorithm?

01Algorithms in Daily Life

Making an Omelette

Driving to School

Key Insight

02Characteristics of a Good Algorithm

Clear & Unambiguous

Well-Defined Inputs

Well-Defined Outputs

Finite Steps

Effective

Language Independent

03Example: Algorithm to Add Two Numbers

Algorithm Steps:

C Code:

04Example: Find Largest of Three Numbers

Algorithm:

Test Your Algorithm!

04bWays to Represent Algorithms

Natural Language

Flowcharts

Pseudocode

# Structured English

Which Format Should I Use?

04cWhy Algorithm Efficiency Matters

Example: Finding a Number in a List

Slow: Check Every Element