Introduction to Problem Solving Class 11 Notes | CBSE Computer Science
Latest Problem Solving Class 11 Notes includes Problem Solving, steps, algorithm and its need, flow chart, pseudo code with lots of examples.
- 1 What is Problem Solving?
- 2 Steps for problem solving
- 3 What is Algorithm?
- 4 Why do we need Algorithm?
- 5.1 Flow chart
- 5.2 Flow Chart Examples
- 5.3 Pseudo code
- 5.4 Pseudo Code Example
- 6.1 Selection
- 6.2 Algorithm, Pseudocode, Flowchart with Selection ( Using if ) Examples
- 6.3 Repetition
- 6.4 Algorithm, Pseudocode, Flowchart with Repetition ( Loop ) Examples
- 7 Decomposition
What is Problem Solving?
Problem solving is the process of identifying a problem, analyze the problem, developing an algorithm for the identified problem and finally implementing the algorithm to develop program.
Steps for problem solving
There are 4 basic steps involved in problem solving
Analyze the problem
- Developing an algorithm
- Testing and debugging
Analyzing the problem is basically understanding a problem very clearly before finding its solution. Analyzing a problem involves
- List the principal components of the problem
- List the core functionality of the problem
- Figure out inputs to be accepted and output to be produced
Developing an Algorithm
- A set of precise and sequential steps written to solve a problem
- The algorithm can be written in natural language
- There can be more than one algorithm for a problem among which we can select the most suitable solution.
Algorithm written in natural language is not understood by computer and hence it has to be converted in machine language. And to do so program based on that algorithm is written using high level programming language for the computer to get the desired solution.
Testing and Debugging
After writing program it has to be tested on various parameters to ensure that program is producing correct output within expected time and meeting the user requirement.
There are many standard software testing methods used in IT industry such as
- Component testing
- Integration testing
- System testing
- Acceptance testing
What is Algorithm?
- A set of precise, finite and sequential set of steps written to solve a problem and get the desired output.
- Algorithm has definite beginning and definite end.
- It lead to desired result in finite amount of time of followed correctly.
Why do we need Algorithm?
- Algorithm helps programmer to visualize the instructions to be written clearly.
- Algorithm enhances the reliability, accuracy and efficiency of obtaining solution.
- Algorithm is the easiest way to describe problem without going into too much details.
- Algorithm lets programmer understand flow of problem concisely.
Characteristics of a good algorithm
- Precision — the steps are precisely stated or defined.
- Uniqueness — results of each step are uniquely defined and only depend on the input and the result of the preceding steps.
- Finiteness — the algorithm always stops after a finite number of steps.
- Input — the algorithm receives some input.
- Output — the algorithm produces some output.
What are the points that should be clearly identified while writing Algorithm?
- The input to be taken from the user
- Processing or computation to be performed to get the desired result
- The output desired by the user
Representation of Algorithm
An algorithm can be represented in two ways:
Pseudo code
- Flow chart is visual representation of an algorithm.
- It’s a diagram made up of boxes, diamonds and other shapes, connected by arrows.
- Each step represents a step of solution process.
- Arrows in the follow chart represents the flow and link among the steps.
Flow Chart Examples
Example 1: Write an algorithm to divide a number by another and display the quotient.
Input: Two Numbers to be divided Process: Divide number1 by number2 to get the quotient Output: Quotient of division
Step 1: Input a two numbers and store them in num1 and num2 Step 2: Compute num1/num2 and store its quotient in num3 Step 3: Print num3
- Pseudo code means ‘not real code’.
- A pseudo code is another way to represent an algorithm. It is an informal language used by programmer to write algorithms.
- It does not require strict syntax and technological support.
- It is a detailed description of what algorithm would do.
- It is intended for human reading and cannot be executed directly by computer.
- There is no specific standard for writing a pseudo code exists.
Keywords used in writing pseudo code
Pseudo Code Example
Example: write an algorithm to display the square of a given number.
Input, Process and Output Identification
Input: Number whose square is required Process: Multiply the number by itself to get its square Output: Square of the number
Step 1: Input a number and store it to num. Step 2: Compute num * num and store it in square. Step 3: Print square.
INPUT num COMPUTE square = num*num PRINT square
Example: Write an algorithm to calculate area and perimeter of a rectangle, using both pseudo code and flowchart.
INPUT L INPUT B COMPUTER Area = L * B PRINT Area COMPUTE Perimeter = 2 * ( L + B ) PRINT Perimeter
Flow of Control
An algorithm is considered as finite set of steps that are executed in a sequence. But sometimes the algorithm may require executing some steps conditionally or repeatedly. In such situations algorithm can be written using
Selection in algorithm refers to Conditionals which means performing operations (sequence of steps) depending on True or False value of given conditions. Conditionals are written in the algorithm as follows:
If <condition> then Steps to be taken when condition is true Otherwise Steps to be taken when condition is false
Algorithm, Pseudocode, Flowchart with Selection ( Using if ) Examples
Example: write an algorithm, pseudocode and flowchart to display larger between two numbers
INPUT: Two numbers to be compared PROCESS: compare two numbers and depending upon True and False value of comparison display result OUTPUT: display larger no
STEP1: read two numbers in num1, num2 STEP 2: if num1 > num2 then STEP 3: display num1 STEP 4: else STEP 5: display num2
INPUT num1 , num2 IF num1 > num2 THEN PRINT “num1 is largest” ELSE PRINT “num2 is largest” ENDIF
Example: write pseudocode and flowchart to display largest among three numbers
INPUT: Three numbers to be compared PROCESS: compare three numbers and depending upon True and False value of comparison display result OUTPUT: display largest number
INPUT num1, num2, num3 PRINT “Enter three numbers” IF num1 > num2 THEN IF num1 > num3 THEN PRINT “num1 is largest” ELSE PRINT “num3 is largest” END IF ELSE IF num2 > num3 THEN PRINT “num2 is largest” ELSE PRINT “num3 is largest” END IF END IF
- Repetition in algorithm refers to performing operations (Set of steps) repeatedly for a given number of times (till the given condition is true).
- Repetition is also known as Iteration or Loop
Repetitions are written in algorithm is as follows:
While <condition>, repeat step numbers Steps to be taken when condition is true End while
Algorithm, Pseudocode, Flowchart with Repetition ( Loop ) Examples
Example: write an algorithm, pseudocode and flow chart to display “Techtipnow” 10 times
Step1: Set count = 0 Step2: while count is less than 10, repeat step 3,4 Step 3: print “techtipnow” Step 4: count = count + 1 Step 5: End while
SET count = 0 WHILE count<10 PRINT “Techtipnow” Count = count + 1 END WHILE
Example: Write pseudocode and flow chart to calculate total of 10 numbers
Step 1: SET count = 0, total = 0 Step 2: WHILE count < 10, REPEAT steps 3 to 5 Step 3: INPUT a number in var Step 4: COMPUTE total = total + var Step 5: count = count + 1 Step 6: END WHILE Step 7: PRINT total
Example: Write pseudo code and flow chart to find factorial of a given number
Step 1: SET fact = 1 Step 2: INPUT a number in num Step 3: WHILE num >=1 REPEAT step 4, 5 Step 4: fact = fact * num Step 5: num = num – 1 Step 6: END WHILE Step 7: PRINT fact
Decomposition
- Decomposition means breaking down a complex problem into smaller sub problems to solve them conveniently and easily.
- Breaking down complex problem into sub problem also means analyzing each sub problem in detail.
- Decomposition also helps in reducing time and effort as different subprograms can be assigned to different experts in solving such problems.
- To get the complete solution, it is necessary to integrate the solution of all the sub problems once done.
Following image depicts the decomposition of a problem
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Chapter 4 Class 11 - Introduction to Problem Solving
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Do you want to learn how to solve problems using computers? Do you want to develop your logical thinking and programming skills ? Do you want to explore the fascinating world of algorithms and data structures ? If you answered yes to any of these questions, then this chapter is for you! 🙌
In this chapter, you will learn about the basic concepts and techniques of problem solving using computers. You will learn how to:
- Define a problem and its specifications 📝
- Analyze a problem and identify its inputs, outputs and processing steps 🔎
- Design an algorithm to solve a problem using various methods such as pseudocode, flowcharts and decision tables 📊
- Implement an algorithm using a programming language such as Python 🐍
- Test and debug your program to ensure its correctness and efficiency 🛠️
- Evaluate your solution and compare it with other possible solutions 💯
By the end of this chapter, you will be able to apply your problem solving skills to various domains such as mathematics, science, engineering, games, art and more. You will also be able to appreciate the beauty and elegance of algorithms and data structures, and how they can help you solve complex and challenging problems. 😍
This chapter is designed for students who have some basic knowledge of computers and programming, but want to improve their problem solving abilities. It is also suitable for anyone who is interested in learning more about computer science and its applications. 🚀
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"Computer Science is a science of abstraction -creating the right model for a problem and devising the appropriate mechanizable techniques to solve it." -A. Aho and J. Ullman Chapter 4 Introduction to Problem Solving In this chapter » Introduction » Steps for Problem Solving » Algorithm » Representation of Algorithms » Flow of Control
COMP1405/1005 - An Introduction to Computer Science and Problem Solving Fall 2011 - 4- There are also other types of programming languages such as functional programming languages and logic programming languages. According to the Tiobe index (i.e., a good site for ranking the popularity of programming languages), as of February 2011 the 10 most
Heuristics for solving problems ''in the small'' (classical math and word problems), generating potential solutions to ''real-life'' problems encountered in the profession, and problem solving in teams. Having successfully completed this course, the student will be able to: Identify skills and personality traits of successful problem solving ...
Steps for problem solving. There are 4 basic steps involved in problem solving. Analyze the problem; Developing an algorithm; Coding; Testing and debugging; Analyze the problem. Analyzing the problem is basically understanding a problem very clearly before finding its solution. Analyzing a problem involves. List the principal components of the ...
Name and explain the steps in the problem-solving process. Solve a problem by applying the problem-solving process. Explain what the word algorithm means. Outline of the Lesson: Candy bar activity (25 minutes) Discussion of solutions (10 minutes) Introduction of the steps in the problem-solving process (15 minutes)
Using NCERT Class 11 Computer Science solutions Introduction to Problem Solving exercise by students is an easy way to prepare for the exams, as they involve solutions arranged chapter-wise and also page-wise. The questions involved in NCERT Solutions are essential questions that can be asked in the final exam.
Introduction to Problem Solving in Computer Science CS 2104 I -- Catalogue Description This course introduces the student to a broad range of heuristics for solving problems in a range of settings that are relevant to computation. Emphasis on problem-solving techniques that aid programmers and computer scientists.
CS2104: Introduction to Problem Solving Fall 2016 Layne T. Watson Departments of Computer Science, Mathematics, ... "Puzzle-based learning for engineering and computer science," IEEE Computer, 43(4), 2010, pp. 20--28. Errors in Reasoning • Goal: Identify common types of errors and avoid them. • Many of these come up in the WASI
By the end of this chapter, you will be able to apply your problem solving skills to various domains such as mathematics, science, engineering, games, art and more. You will also be able to appreciate the beauty and elegance of algorithms and data structures, and how they can help you solve complex and challenging problems. 😍
The audience for 1.00 is non-computer science majors. 1.00 does not focus on writing compilers or parsers or computing tools where the computer is the system; it focuses on engineering problems where the computer is part of the system, or is used to model a physical or logical system.