Lecture 3: Problem Solving, Algorithms, Pseudocode, and Flowcharts

Problem Solving in Computer Science

• Solving problems is the core of computer science
• Programmers must understand how humans solve problems, then translate solutions into computer-executable algorithms
• Machines may solve problems differently than humans

Stages of Problem Solving

1. Analyzing the problem
2. Writing algorithm steps (pseudocode & flowcharts)
3. Writing the program in a programming language
4. Translating to machine code
5. Executing, testing, and debugging
6. Documenting the software

Algorithms

Definition: A set of rules and procedures for solving a problem in finite steps

Characteristics of a Good Algorithms:

• Each step must be clear and unambiguous
• Steps described using precise language
• Must terminate after finite steps
• Must lead to correct solution

Algorithm Representation Methods

Pseudocode

• Uses English-like phrases to outline programs
• Focuses on solution steps rather than syntax
• Easily convertible to actual programming code

Statement Structures:

// Sequential Statements - executed in order
SET x = 5
SET y = 10
SET result = x + y

// Decision Statements
IF temperature > 30 THEN
  PRINT "It's hot"
ELSE
  PRINT "It's cool"
END IF

// Looping Statements
SET i = 1
WHILE i <= 5 DO
  PRINT i
  SET i = i + 1
END WHILE

Flowcharts

• Graphical representation of process steps using standardized symbols

Key Symbols

1. Oval: Start/End points
2. Arrow: Direction of flow
3. Rectangle: Process steps
4. Diamond: Decision points
5. Parallelogram: Input/Output (I/O)
6. Connector Points: Connect different chart parts
7. Text Label: Describe actions/decisions
8. Hexagon: For loops (initial condition, increment, termination)

Flowchart Guidelines

• Must be neat, complete, easy to follow, and unambiguous
• Natural direction: left to right, top to bottom
• Clear flow lines with proper connections

Advantages

• Communication: Standard symbols facilitate understanding
• Action Analysis: Effective problem analysis
• Documentation: Important documentation tool
• Efficient Coding: Aids program writing
• Error Detection: Easy to trace and identify errors
• Program Correction: Easier debugging and fixes

Disadvantages

• Complexity: Can become complex for large problems
• Modifications: Changes may require redrawing
• Copying Issues: Difficult to reproduce if symbols are hard to draw
• Detail Overload: Excessive details can obscure main solution

Code Examples

Adding Two Numbers

BEGIN
  INPUT first number (N1)
  INPUT second number (N2)
  SET Sum = N1 + N2
  OUTPUT Sum
END

Circle Area and Perimeter

BEGIN
  SET PI = 3.14
  INPUT Radius
  SET Area = PI * Radius * Radius
  SET Perimeter = 2 * PI * Radius
  OUTPUT Area, Perimeter
END

Finding Maximum of Three Numbers

BEGIN
  INPUT A, B, C
  IF A > B THEN
    IF A > C THEN
      PRINT "A is largest"
    ELSE
      PRINT "C is largest"
    END IF
  ELSE
    IF B > C THEN
      PRINT "B is largest"
    ELSE
      PRINT "C is largest"
    END IF
  END IF
END

Printing First Five Natural Numbers

BEGIN
  SET i = 1
  WHILE i <= 5 DO
    PRINT i
    SET i = i + 1
  END WHILE
END

Repetition Structures

• Pre-test loop: Condition checked at beginning (while)
• Post-test loop: Condition checked at end (do-while)
• Each loop must have a termination condition