Foundation of Programming (AQA)

Data Types

Data Types

Specifies the kind of data that can be stored and manipulated within a program. Examples: integers, real numbers, Booleans, characters, and strings.

Integer

Whole numbers without a fractional part, used for counting and indexing. Example: 5, -42

Real (Float)

Numbers that can contain a fractional part, used for measurements and continuous data. Example: 3.14, -0.001

Boolean

Represents true or false values, used for logical operations and conditional statements. Example: True, False

Character

A single alphanumeric character, used for text processing at a granular level. Example: 'A', '3'

String

A sequence of characters, used for text and sentences. Example: "Hello", "123ABC"

Variable Declaration

Introduces a variable by specifying its name and type. Example: age = 25

Constant Declaration

Defines a value that cannot be changed during program execution. Example: PI = 3.14159

Assignment

Assigns a value to a variable. Example: name = "Alice"

Iteration

Repeats a block of code multiple times or until a condition is met.

Selection

Makes decisions within a program based on conditions. Example: score = 85

Subroutine (Procedure/Function)

Encapsulates a block of code that performs a specific task. Example: def calculate_area(width, height): return width * height

Sequence

Default mode of execution where statements run one after the other.

Nested Iteration

Repeats a sequence of instructions within another iteration.

Nested Selection

Makes decisions within a program based on conditions within another selection.

Named Constants and Variables

Used to make programs easier to read and maintain. Constants ensure values do not change accidentally, while variables hold data that can change.

Meaningful Identifier Names

Improve code readability and maintainability by using descriptive names and consistent naming conventions. Examples: total_sum, user_age, calculate_area

Arithmetic Operations in Programming

Include addition, subtraction, multiplication, real division, integer division, and remainders.

Modular Arithmetic

Used in scenarios requiring periodicity, such as clock arithmetic.

Relational Operations

Include common relational operators like Equal To, Not Equal To, Less Than, Greater Than, Less Than or Equal To, and Greater Than or Equal To.

Boolean Operations

Include common Boolean operators like NOT, AND, and OR.

Data Structures

Ways of organizing and storing data efficiently. Examples: Arrays, Records (Structures).

Records

Used to group different data types under one name, allowing for a structured way to represent real-world entities.

Arrays

A collection of elements of the same type, stored in contiguous memory locations.

One-Dimensional Array

Example: numbers = [1, 2, 3, 4, 5]

Two-Dimensional Array

Example: matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

Efficiency

Data structures like arrays allow for efficient storage and retrieval of data.

Organization

Records provide a structured way to store related data fields.

Simplicity

Arrays and records simplify the implementation of algorithms and data manipulation operations.

User Input

Obtaining user input from the keyboard in Python using the input() function.

Output Data

Using the print() function in Python to display data and information on the computer display.

Length

Using the len() function in Python to get the length of a string.

Position

Accessing individual characters in a string by their position using zero-based indexing.

Substring

Extracting a part of a string.

Concatenation

Joining two strings together.

Convert Character to Character Code

Using ord() to get the ASCII value of a character and chr() to get the character from an ASCII value.

String Conversion Operations

Converting between different data types like string to integer, real to string, etc.

Generating Random Integer

A specified range using randint() to generate a number from the random module.

Generating Random Float

Generating a random number between 0.0 and 1.0 using the random() function.

Random Choice from a Sequence

Choosing a random element using the choice() function.

Shuffling a Sequence

Randomly shuffling the elements of a sequence using the shuffle() function.

Simulation

Simulating random events or behaviors.

Games

Generating random game scenarios, outcomes, or choices.

Statistical Sampling

Generating random samples for statistical analysis.

Cryptographic Applications

Creating cryptographic keys or initialization vectors.

Subroutine

A named 'out of line' block of code that can be executed by writing its name in a program statement.

Procedures

Subroutines that perform actions but do not return a value.

Functions

Subroutines that perform actions and return a value.

Modularity

Breaks programs into manageable sections. Each subroutine performs a specific task, making it easier to understand and manage.

Simplified Maintenance

Easier to update and fix code. Changes in a subroutine affect all calls to it, reducing the need to make multiple updates.

Improved Readability

Makes code more organized and easier to understand. Subroutines give structure and clarify the purpose of each part of the code.

Enhanced Collaboration

Different programmers can work on different subroutines simultaneously. This is particularly useful in large projects.

Parameters

Variables listed as part of a subroutine's definition, allowing data to be passed into the subroutine.

Data Passing by Value

A copy of the data is passed to the subroutine.

Data Passing by Reference

A reference to the actual data is passed, allowing modifications.

Returning Values from Subroutines

Subroutines can return a value to the calling routine using the return statement.

Local Variables in Subroutines

Variables declared within a subroutine, accessible only within that subroutine.

Structured Approach

A method of programming that emphasizes breaking a program into smaller, manageable, and reusable modules or subroutines.

Common Validation Checks

Includes minimum length check, empty string check, and range check for validating input data.

Simple Authentication Routines

Example of an authentication routine that checks username and password for validity.

Testing

Involves running a program to find errors or confirm expected behavior under different conditions.

Types of Errors

Syntax errors and logic errors are common types of errors in programming.

Records (Structures)

Used to group different data types under one name, allowing for a structured way to represent real-world entities. This is akin to a form where different fields (like name, address, phone number) are filled out for each individual.

Syntax Error

Errors due to incorrect code syntax

Logic Error

Errors where program runs but produces incorrect results