COMPUTATIONAL THINKING AND PROGRAMMING LOGIC

Simple Study Notes from Section 4

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1. ALGORITHMS

What is an Algorithm?

An algorithm is a series of steps that you follow to solve a problem or complete a task. Think of it like a recipe in cooking that tells you what to do, step by step.

Key Characteristics of Algorithms

1. Input - The data the user enters to start the process
2. Output - The result or solution based on the given inputs
3. Definiteness - Each step must be precise and clear
4. Finiteness - Must have a finite number of steps and eventually end
5. Effectiveness - Steps should be simple and executable
6. Language Independence - Can be implemented in any programming language

Types of Algorithms

1. Sorting Algorithms - Arrange elements in order (e.g., alphabetical)
2. Mathematical Algorithms - Perform calculations (average, sum, area)
3. Encryption Algorithms - Encode data for security
4. Search Algorithms - Find specific elements in data

Real-Life Algorithm Example

Visual Representation: Algorithm Process

Simple Math Algorithm Example

Problem: Find the sum of 529 and 256

Pseudocode:

1. Assign x the value 529
2. Assign y the value 256
3. Assign z the sum of x and y
4. Output the value of z

Python Code:

x = 529
y = 256
z = x + y
print(z)

Output: 785

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2. VARIABLES

What is a Variable?

Variables are named storage locations that hold a value or an object which can be changed.

Think of variables as labeled boxes that store information in your program.

Key Points about Variables

• Variables have names (identifiers) - e.g., x, y, total, name
• Variables store values - e.g., 529, "Hello", 3.14
• Variable values can change during program execution
• In Python, use lowercase letters for variable names

Assignment Operator

The assignment operator in Python is the "=" symbol.

Examples:

age = 16
reply = True
cost = 34.56
city = "Kumasi"
console = 'PlayStation'

Example: Using Variables

message = "Python is fun"
print(message)

information = "My message to you is "
print(information + message)  # Join variables with +

Output:

Python is fun
My message to you is Python is fun

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3. FLOWCHARTS

What is a Flowchart?

Flowcharts are graphical representations of algorithms that use shapes and arrows to illustrate the sequence of steps in an algorithm.

While pseudocode uses plain text to show steps, flowcharts use shapes to solve the same problem.

Basic Flowchart Symbols

Symbol	Name	Function
Oval (rounded rectangle)	Terminator	Shows where a process begins or ends (START/STOP)
Rectangle	Processing	Shows actions or operations (calculations, assignments)
Parallelogram	Input/Output	Shows data being entered (input) or displayed (output)
Diamond	Decision	Shows a choice or condition with different outcomes
Arrow	Flow Lines	Shows the order of instructions and connections
Circle	On-page Connector	Links different parts on the same page
Pentagon	Off-page Connector	Shows flow continues on another page

Flowchart Symbols Visual Reference

Flowchart Example: Addition Algorithm

Why Use Flowcharts?

• Visual and easy to understand
• Shows the logic flow clearly
• Great for planning before coding
• Helps identify errors in logic

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4. DATA STRUCTURES

What are Data Structures?

Data structures are used to organize and store collections of data in a way that makes it easy to access and modify.

They are like building blocks that allow programmers to efficiently store, retrieve, and manipulate data in computer programs.

Importance of Data Structures

1. Organize and store data efficiently
2. Enable efficient storage and retrieval of data
3. Reduce processing time and improve performance
4. Essential for becoming a programmer
5. Allow you to write more efficient code

Classifications of Data Structures

1. LINEAR DATA STRUCTURES

Definition: Data elements are arranged in a sequential, end-to-end manner. Each element has predecessors and successors (except first and last).

Characteristics:

• Items are related to previous and next items
• Data arranged in linear sequence
• Can be traversed in a single run
• Implementation is easy

Examples:

• Arrays
• Stacks
• Queues
• Linked Lists

2. NON-LINEAR DATA STRUCTURES

Definition: Data elements are not organized sequentially but in an interconnected manner.

Characteristics:

• Every item is attached to many other items
• Data is NOT arranged in sequence
• Cannot be traversed in a single run
• Implementation is difficult
• May have faster access time but require more memory

Examples:

• Trees (like organization hierarchy)
• Graphs (like social media connections)

Comparison Table

Criteria	Linear	Non-Linear
Data Arrangement	Sequential (one after another)	Hierarchical or interconnected
Links	Each item linked to previous and next	Each item linked to many items
Traversing	Single run possible	Multiple paths needed
Implementation	Easy	Difficult
Examples	Arrays, Stacks, Queues	Trees, Graphs

Visual Comparison: Linear vs Non-Linear Data Structures

Other Classifications

Static vs Dynamic Data Structures

Static Data Structures:

• Have a fixed size
• Memory allocated at compile time
• Size cannot be changed after compilation
• Example: Arrays

Dynamic Data Structures:

• Have a size that can change
• Memory allocated at runtime
• Can grow or shrink as needed
• Example: Linked Lists

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5. ARRAYS (Linear Data Structure)

What is an Array?

An array is a collection of elements stored in contiguous memory locations. Each element can be accessed by its index (position).

Array Structure Visualization

Example Array in Python

# Creating an array
foods = ["Akple", "Fufu", "Kenkey", "Banku"]

# Accessing elements by index (starts at 0)
print(foods[0])  # Output: Akple
print(foods[2])  # Output: Kenkey

Array Operations

1. Reverse - Reverse the order of elements
2. Sort - Arrange elements in order
3. Search - Find specific elements
4. Count - Count occurrences of an element
5. Copy - Duplicate the array

Example: Reversing an Array

activities = ["Morning jog", "Breakfast", "Study"]
print("Original:", activities)

# Reverse the array
activities.reverse()

# Output each element
for activity in activities:
    print(activity)

Output:

Original: ['Morning jog', 'Breakfast', 'Study']
Study
Breakfast
Morning jog

Example: Counting Occurrences

computerList = ["tablet", "desktop", "tablet",
                "smartphone", "supercomputer", "tablet"]

# Count specific items
toCheck1 = "tablet"
toCheck2 = "mainframe"

print("Number of", toCheck1, ":", computerList.count(toCheck1))
print("Number of", toCheck2, ":", computerList.count(toCheck2))

Output:

Number of tablet: 3
Number of mainframe: 0

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6. THREE ALGORITHM REPRESENTATIONS

The same algorithm can be represented in THREE different ways:

1. Pseudocode

• Description: Written instructions in plain English-like language
• Best For: Planning and communication
• Advantage: Language independent, easy to understand

2. Flowchart

• Description: Visual diagram with shapes and arrows
• Best For: Understanding logic flow
• Advantage: Shows flow clearly, visual representation

3. Program Code

• Description: Actual programming language (like Python)
• Best For: Computer execution
• Advantage: Can be run by computer, produces actual results

Key Insight

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7. SWAP ALGORITHM

What is Swapping?

The swap algorithm is used to exchange the values of two variables without losing data.

Real-World Analogy

Swap Algorithm Steps

1. Temp = A - Store first value in temporary variable
2. A = B - Copy second value to first variable
3. B = Temp - Copy temporary value to second variable

Python Code Example

# Swap Algorithm
a = 49
b = 61
print("Original values:", a, "and", b)

# Swap using temporary variable
temp = a
a = b
b = temp

print("After swap:", a, "and", b)

Output:

Original values: 49 and 61
After swap: 61 and 49

Why Use a Temporary Variable?

Visual Representation: Swap Algorithm

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KEY CONCEPTS SUMMARY

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REMEMBER