Course Module: Advanced Test Design Techniques & Code-Level Testing

Module Goal

This module enhances software testing skills by introducing advanced techniques for effective test design and code testing.

What You'll Learn (Learning Objectives)

This section outlines the learning objectives for the module on advanced test design techniques.

Lecture 51: Combinatorial Testing - Smartly Testing Many Combinations

This section covers the challenges of combinatorial explosion in testing and introduces Combinatorial Testing techniques, focusing on Pairwise Testing for efficient bug detection.

The Challenge Of 'combinatorial Explosion'

This section discusses the issue of combinatorial explosion in software testing, highlighting the limitations of exhaustive testing and introducing combinatorial testing as an efficient alternative.

The Problem Explained

This section addresses the challenge of 'combinatorial explosion' in software testing and introduces Combinatorial Testing as an effective solution.

Why Exhaustive Testing Is Impractical

Exhaustive testing, which involves testing all possible combinations of inputs, is often impractical due to combinatorial explosion, resource constraints, and inefficiency in detecting most bugs.

What Is Combinatorial Testing?

Combinatorial Testing is a technique aimed at efficiently testing software by focusing on specific value combinations of parameters to identify defects caused by interactions between inputs.

Simply Put

This section introduces combinatorial testing methods, focusing on efficiently handling input combinations and uncovering interaction bugs.

The Core Principle

This section introduces the fundamental challenges of software testing, specifically focusing on combinatorial explosion and the core principles of testing techniques like Pairwise Testing.

Coverage Levels (N-Way Coverage)

This section discusses Coverage Levels, focusing on Combinatorial Testing techniques such as pairwise and N-way coverage methods to manage testing complexity.

How Combinatorial Testing Works (The Process)

This section outlines the process of combinatorial testing, providing an effective approach to managing and executing tests for systems with multiple inputs by leveraging optimized coverage techniques.

Simplified Example: Configuring A Software Installation

This section explains the principles of Combinatorial Testing with a focus on Pairwise Testing, illustrating the efficiency of testing software installations through a structured approach.

Benefits Of Combinatorial Testing

Combinatorial Testing offers an efficient methodology for software testing, drastically reducing the number of test cases needed while maintaining robust coverage.

Key Takeaway

This section emphasizes the importance of sophisticated test design techniques, highlighting concepts like combinatorial testing, decision table testing, cause-effect graphing, pairwise testing, and white-box testing.

Lecture 52: Decision Table Testing - Turning Rules Into Powerful Tests

This section introduces Decision Table Testing, a structured approach to designing test cases from complex business rules to ensure comprehensive testing of outcomes.

The Challenge Of Complex Rules

This section addresses the challenges of testing software with complex business rules and introduces systematic techniques like Combinatorial Testing, Decision Table Testing, and Cause-Effect Graphing to tackle these complexities.

What Is A Decision Table?

A Decision Table is a systematic tool for analyzing complex business rules and conditions to ensure complete test coverage.

Simply Put

This section introduces sophisticated testing techniques, particularly focusing on combinatorial testing and its practical applications in software testing.

Purpose Of Using Decision Tables

Decision tables provide a structured approach to managing complex business rules, helping ensure comprehensive test coverage and clarity.

Components Of A Decision Table

This section introduces Decision Tables as a structured method for managing complex business rules and ensuring comprehensive testing.

Steps To Create A Decision Table

Decision Tables provide a structured approach to managing complex business rules in software testing by representing all possible condition combinations and their corresponding outcomes.

Detailed Example: Flight Booking Discount Policy

This section illustrates Decision Table Testing through the Flight Booking Discount Policy, demonstrating how it helps clarify complex business rules and ensures comprehensive test coverage.

Benefits Of Decision Table Testing

Decision Table Testing is a valuable technique that clarifies complex business rules, ensuring comprehensive test coverage and systematic test case generation.

Key Takeaway

This section provides an overview of advanced testing techniques for software, emphasizing their importance in efficiently identifying bugs in complex systems.

Lecture 53: Cause-Effect Graphing - Visualizing Logic For Deeper Tests

Cause-Effect Graphing is a visual approach to clarify complex logic in software requirements, aiding in effective test case generation.

The Problem: Complex Logic And Ambiguous Language

This section discusses the challenges of testing software systems that have complex logic and ambiguous language, highlighting combinatorial testing and decision table techniques as solutions.

What Is Cause-Effect Graphing?

Cause-Effect Graphing is a visual technique that maps logical relationships between inputs and outputs, aiding in the systematic creation of test cases.

Simply Put

This section discusses advanced testing techniques focused on combinatorial testing and decision tables, emphasizing efficient test case generation.

Purpose Of Using Cause-Effect Graphs

Cause-Effect Graphing is a visual tool that helps clarify complex system requirements by mapping input conditions to their corresponding effects, facilitating systematic test case generation.

Key Elements Of A Cause-Effect Graph

Cause-Effect Graphing is a visual technique to analyze logical relationships between input conditions and system outputs, aiding in systematic test derivation.

Steps To Create And Use A Cause-Effect Graph

Cause-Effect Graphing is a visual technique that helps map logical relationships between inputs and outputs to derive complex test cases.

Detailed Example: User Login With Account Status

Benefits Of Cause-Effect Graphing

Cause-Effect Graphing provides a systematic way to visualize and analyze relationships between inputs and outputs, ensuring comprehensive test case development.

Key Takeaway

This section highlights the importance of combinatorial testing methods, particularly pairwise testing, as essential strategies for designing efficient tests that ensure comprehensive coverage without exhaustive combinations.

Lecture 54: Pairwise Testing - The Power Of Two For Efficient Coverage

Pairwise Testing is an efficient technique in combinatorial testing focused on covering interactions between pairs of parameters to identify defects.

Why Pairwise Testing Is So Important (The '2-Problem')

Pairwise Testing effectively reduces the number of test cases needed to identify defects caused by interactions between pairs of parameters.

What Is Pairwise Testing?

Pairwise Testing is an efficient testing technique that ensures all possible pairs of input parameters are covered in test cases, thus efficiently detecting bugs that arise from interactions between two variables.

Simply Put

Combinatorial Testing effectively reduces the number of test cases needed to find bugs by focusing on parameter interactions.

The Efficiency Gain

This section introduces combinatorial testing and its efficiency in addressing the problem of combinatorial explosion in software testing.

How Pairwise Testing Works (The Process, Not Manual)

Pairwise Testing is a systematic approach that optimally reduces test cases while ensuring comprehensive coverage of all possible value pairs across system parameters.

Detailed Example: Testing A Web Application Login Across Environments

When To Use Pairwise Testing (Practical Applications)

Pairwise testing efficiently identifies interaction bugs by covering every possible pair of input values, thereby reducing overall test cases.

Benefits Of Pairwise Testing

Pairwise Testing is a vital technique in software testing that focuses on efficiently identifying interaction bugs by ensuring every possible combination of parameter pairs is tested, significantly reducing the overall number of test cases.

Key Takeaway

This section highlights the significance of combinatorial testing methodologies, particularly pairwise testing, in optimizing software test design for complex systems.

Lecture 55: White-Box Testing - Examining The Code's Inner Workings

White-Box Testing involves examining the internal workings of a codebase, ensuring every internal part functions correctly.

What Is White-Box Testing?

White-Box Testing is a method of testing software that examines the internal structures or workings of an application, as opposed to its functionality.

When And Who Performs White-Box Testing?

White-Box Testing, also known as structural testing, focuses on the internal structure of the code. This section discusses when and by whom this type of testing is typically performed.

Key White-Box Testing Techniques (Code Coverage Metrics)

This section explores key white-box testing techniques focused on code coverage metrics, emphasizing the importance of assessing internal code quality and testing effectiveness.

Code Coverage Tools

This section explores code coverage tools and their importance in evaluating the effectiveness of white-box testing by measuring how much code has been exercised during testing.

Benefits Of White-Box Testing

White-Box Testing offers insights into the internal workings of the software to ensure all paths in the code are tested, leading to improved software quality.

Limitations Of White-Box Testing

White-Box Testing is crucial for validating internal logic but has inherent limitations such as developer skill requirements and lack of user requirement validation.

Key Takeaway

This section emphasizes the importance of advanced testing techniques like combinatorial testing, decision table testing, and white-box testing in ensuring software quality.