Area 2.12

Testing

Master comprehensive testing methodologies including unit, integration, system, performance, usability, and regression testing. Learn to design effective test cases and execution strategies.

10+

Test Types

Core Methods

~2.5hrs

Study Time

Learning Objectives

Understand different testing methodologies and their purposes
Design effective test data for various testing scenarios
Apply unit, integration, and system testing approaches
Implement performance, usability, and regression testing
Develop comprehensive test plans and execution strategies

Core Testing Approaches

Unit Testing

Testing individual components or functions in isolation

Purpose:

Verify that each unit of code performs as expected

Example:

Testing a single function like calculate_tax()

Advantages:

Fast execution
Easy to debug
Good for TDD

Python Example:

def calculate_tax(amount, rate):
    return amount * rate

# Unit test
def test_calculate_tax():
    assert calculate_tax(100, 0.1) == 10.0
    assert calculate_tax(0, 0.1) == 0.0
    assert calculate_tax(100, 0) == 0.0

Integration Testing

Testing interactions between integrated components

Purpose:

Ensure different modules work together correctly

Example:

Testing database connection with user authentication

Advantages:

Finds interface issues
Tests real interactions
Validates data flow

Python Example:

def test_user_registration():
    # Test integration between user input, validation, and database
    user_data = {"name": "Alice", "email": "alice@test.com"}
    
    # This tests multiple components working together
    user_id = register_user(user_data)
    stored_user = get_user_from_database(user_id)
    
    assert stored_user["name"] == "Alice"

System Testing

Testing complete integrated system functionality

Purpose:

Verify entire system meets specified requirements

Example:

Testing complete e-commerce checkout process

Advantages:

End-to-end validation
Real-world scenarios
User perspective

Python Example:

def test_complete_checkout_process():
    # System test covering entire user journey
    login_user("test_user", "password")
    add_item_to_cart("laptop", quantity=1)
    enter_shipping_address(address_data)
    process_payment(card_data)
    
    # Verify system state after complete process
    order = get_latest_order()
    assert order["status"] == "confirmed"

Testing Methodologies

Performance Testing

Load Testing

Test normal expected load

Example: 100 concurrent users

Stress Testing

Test beyond normal capacity

Example: 1000 concurrent users

Volume Testing

Test with large amounts of data

Example: Million records database

Functional Testing

Boundary Testing

Test edge cases and limits

Example: Age input: -1, 0, 150, 999

Acceptance Testing

Verify user requirements met

Example: Customer can complete purchase

Regression Testing

Ensure changes don't break existing features

Example: Re-run all tests after bug fix

Usability Testing

User Interface Testing

Test UI elements and navigation

Example: Button placement, menu accessibility

Accessibility Testing

Ensure usable by people with disabilities

Example: Screen reader compatibility

User Experience Testing

Evaluate overall user satisfaction

Example: Task completion rates

Test Data Design Principles

Equivalence Partitioning

Group inputs into classes that should behave similarly

Example Scenario:

Age groups: Child (0-12), Teen (13-17), Adult (18-65), Senior (65+)

Test Data:

• 5 (Child)
• 15 (Teen)
• 30 (Adult)
• 70 (Senior)

Boundary Value Analysis

Test at the edges of input ranges

Example Scenario:

For age range 18-65, test boundary values

Test Data:

• 17 (just below)
• 18 (minimum)
• 65 (maximum)
• 66 (just above)

Invalid Data Testing

Test with incorrect or malicious inputs

Example Scenario:

Testing form validation with bad data

Test Data:

• Empty strings
• SQL injection attempts
• Extremely long inputs
• Wrong data types

Learning Activities

Test Case Design Workshop

Design

50 minutes

Create comprehensive test cases using equivalence partitioning and boundary analysis

Automated Testing Implementation

Coding

60 minutes

Write and execute unit tests for a sample Python program

Performance Testing Simulation

Analysis

45 minutes

Design and conduct performance tests to identify system bottlenecks

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