Introduction to Problem Solving for Class 11 NCERT Computer Science
By MyStudyCoach Team · Published on 2 July 2026 · 5 min read

Introduction to Problem Solving is a key chapter in Class 11 NCERT Computer Science. It teaches you how to approach and solve problems logically using algorithms, flowcharts, and pseudocode, essential skills for programming and computational thinking.
Understanding the Basics of Problem Solving
Problem solving is the process of finding solutions to complex or simple issues by applying logical thinking and systematic steps. In Class 11 NCERT Computer Science, the first step is to define the problem clearly to understand what needs to be solved. Once the problem is understood, you can devise a plan or algorithm to solve it.
An algorithm is a finite set of well-defined instructions that solve a problem. It is independent of any programming language and focuses on the logic rather than syntax. For example, an algorithm to find the square of a number involves:
- Inputting the number
- Multiplying the number by itself
- Displaying the result
This logical approach helps break down problems into manageable steps, making programming easier and more efficient.
What Is an Algorithm? Definition and Characteristics
An algorithm is a precise sequence of instructions to solve a problem or perform a task. The word 'algorithm' is derived from the name of the Persian mathematician Muhammad ibn Musa al-Khwarizmi.
Key characteristics of an algorithm include:
- Finiteness: It must terminate after a finite number of steps.
- Definiteness: Each step must be clear and unambiguous.
- Input: Zero or more inputs are taken.
- Output: At least one output is produced.
- Effectiveness: Each step should be basic enough to be performed exactly and in finite time.
Algorithms can be expressed in various ways, such as natural language, flowcharts, or pseudocode.
Example: Algorithm to add two numbers:
1. Start 2. Input num1 3. Input num2 4. Compute sum = num1 + num2 5. Print sum 6. End
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Flowcharts: Visual Representation of Algorithms
Flowcharts are graphical diagrams that represent the flow of an algorithm using standardized symbols connected by arrows. They help visualize the sequence and decision-making process clearly.
Common Flowchart Symbols:
| Symbol | Purpose | Description |
|---|---|---|
| Oval | Start/End (Terminator) | Indicates where the flow begins or ends |
| Rectangle | Process | Represents an action or step |
| Diamond | Decision | Represents a condition with branches (Yes/No) |
| Parallelogram | Input/Output | Represents data input or output |
| Arrow | Flow Direction | Shows the order of steps |
Example: Flowchart to calculate the square of a number:
- Start
- Input number
- Multiply number by itself
- Display result
- End
Flowcharts make it easier to communicate algorithms to others and identify logical errors before coding.
Pseudocode: Writing Algorithms in Simple Language
Pseudocode is a human-readable way to write algorithms using plain English and programming-like keywords such as INPUT, COMPUTE, PRINT, IF, ELSE, WHILE, etc. It is not actual code but helps programmers plan the logic clearly.
Advantages of Pseudocode:
- Easy to understand for both programmers and non-programmers
- Helps ensure all steps are included before coding
- Language-independent and flexible
Example: Pseudocode to find the sum of two numbers:
`` INPUT num1 INPUT num2 COMPUTE sum = num1 + num2 PRINT sum ``
Pseudocode focuses on the logic, ignoring syntax rules of programming languages, making it an excellent tool for learning and designing algorithms.
Control Structures in Algorithms: Sequence, Decision, and Iteration
Algorithms use control structures to manage the flow of execution. The three main types are:
1. Sequence: Steps executed one after another in order. 2. Decision (Selection): Branching based on conditions (e.g., IF-ELSE). 3. Iteration (Looping): Repeating steps multiple times (e.g., WHILE, FOR loops).
Example of Decision:
If a number is positive, print "Positive", else print "Non-positive".
Example of Iteration:
Calculate the sum of first 5 natural numbers:
`` sum = 0 for i = 1 to 5 sum = sum + i print sum ``
Understanding these structures helps in designing efficient algorithms and writing effective programs.
Dry Run: Testing Your Algorithm Before Coding
A dry run is a manual process of going through the steps of an algorithm with sample input values to check its correctness. It helps identify logical errors before actual programming.
Steps to Perform a Dry Run:
- Choose sample input values.
- Follow each step of the algorithm carefully.
- Track variable values and outputs.
- Verify if the output matches the expected result.
Example: Dry run for sum of two numbers algorithm with inputs num1=3 and num2=5:
| Step | Action | Variables | Output |
|---|---|---|---|
| 1 | Input num1 | num1 = 3 | |
| 2 | Input num2 | num2 = 5 | |
| 3 | Compute sum = num1+num2 | sum = 8 | |
| 4 | Print sum | 8 |
Dry run ensures the algorithm works as intended and saves time during coding.
Frequently asked questions
What is the first step in problem solving?
The first step is to define the problem clearly to understand what needs to be solved.
What does an algorithm mean?
An algorithm is a step-by-step set of instructions designed to solve a specific problem.
How do flowcharts help in problem solving?
Flowcharts visually represent the sequence and decisions in an algorithm, making logic easier to understand.
What is pseudocode used for?
Pseudocode is used to write algorithm steps in simple, human-readable language before coding.
What is a dry run in algorithms?
A dry run is manually tracing an algorithm with sample inputs to check for correctness.
What are the main control structures in algorithms?
Sequence, decision (selection), and iteration (looping) are the main control structures.
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