Problem Solving Process

Six Steps of Computer-Based Problem Solving

1. Problem Definition

First, we must clearly understand what problem needs to be solved.

We identify:

• What is the input?
• What should be the output?
• What are the constraints?
• What exactly is the objective?

Example

Problem: Find the largest number in a list.

Input  →  [12, 45, 7, 32, 18]
Output →  45

Before writing any code, we must clearly understand what is required.

Key question: What exactly do I need to solve?

---

2. Algorithm Design

Once the problem is understood, we develop a step-by-step procedure to solve it.

For finding the largest number:

1. Assume the first number is the largest.
2. Compare it with the next number.
3. If the next number is larger, make it the largest.
4. Continue until all numbers are checked.
5. Display the largest number.

This is the algorithm.

Key question: How can I solve the problem step by step?

---

3. Implementation

Now we convert the algorithm into a program using a programming language such as Python, C, Java, etc.

For example, the algorithm can be implemented in Python:

numbers = [12, 45, 7, 32, 18]

largest = numbers[0]

for number in numbers:
    if number > largest:
        largest = number

print(largest)

The computer cannot directly execute our informal algorithm. It needs instructions written in a programming language.

Key question: How can I express my algorithm in a programming language?

---

4. Execution

The computer now runs the program.

For the given input:

[12, 45, 7, 32, 18]

the program compares the numbers and produces:

Largest = 45

During execution, the computer:

Input
  ↓
Program instructions
  ↓
Processing
  ↓
Output

Key question: What happens when the computer runs my program?

---

5. Testing and Debugging

A program that runs without a syntax error is not necessarily correct.

We must test it with different inputs.

For example:

Test 1: [12, 45, 7, 32]       → 45 ✓
Test 2: [5, 2, 9, 1]          → 9 ✓
Test 3: [-5, -2, -10]         → -2 ✓
Test 4: [7]                   → 7 ✓

If the program produces an incorrect result, we identify and fix the error.

Common types of errors include:

• Syntax error – incorrect programming language syntax
• Logical error – program runs but produces the wrong answer
• Runtime error – error occurs while the program is running

Key question: Does my program produce the correct result for different inputs?

---

6. Optimization, Documentation and Maintenance

Once the program is working correctly, we can improve it.

Optimization

We ask:

Can the program be made faster or use less memory?

For example, if a program takes too long for a very large input, we may need to design a more efficient algorithm.

Documentation

We explain:

• What the program does
• How the algorithm works
• Important design decisions
• How to use the program

Maintenance

After the program is deployed, we may need to:

• Fix newly discovered bugs
• Add new features
• Modify the program for new requirements
• Improve performance

Key question: Can I make the solution better and maintainable?

---

Complete Process at a Glance

        PROBLEM
           ↓
  1. Define the Problem
           ↓
  2. Design the Algorithm
           ↓
  3. Implement the Algorithm
           ↓
  4. Execute the Program
           ↓
  5. Test & Debug
           ↓
  6. Optimize, Document
     & Maintain
           ↓
       SOLUTION

A Simple Example for Students

Suppose the problem is:

“Calculate the average marks of five students.”

Step	What we do
1. Problem Definition	Input = 5 marks; Output = average
2. Algorithm Design	Add all marks and divide by 5
3. Implementation	Write the program  in Python/C/Java
4. Execution	Run the program with marks
5. Testing & Debugging	Test with different marks and correct errors
6. Optimization & Maintenance	Improve the program and modify it if requirements change

Remember these six questions:

1. What is the problem? → Problem Definition
2. How will I solve it? → Algorithm Design
3. How do I write the solution? → Implementation
4. What happens when I run it? → Execution
5. Is the answer correct? → Testing & Debugging
6. Can I make it better? → Optimization & Maintenance

This gives students a clear connection between problem-solving, algorithmic thinking, and programming.