Difference between Black box and White box testing

The main difference between Black Box and White Box testing is that in black box testing, only the external structure is tested without the knowledge of internal workings. In white box testing, the software's internal working is tested. 

In this article, we will explore the differences between Black Box and White Box testing in depth. But before we do that, let's explore the topics that we will cover in this piece. 

Table of Content (TOC)

•  Difference Between Black Box and White Box Testing - Tabular Comparision
• What is Black Box Testing?
• What is White Box Testing?
• Example of Black Box Testing vs White Box Testing
• Key Differences Between Black Box and White Box Testing

Difference between Black Box and White Box Testing

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What is Black Box Testing?

Black Box Testing or Behavioral Testing is a software technique in which the tester tests an item's (software's) external structure and design. The tester does not know the internal structure, design, and implementation of the software being tested. 

Black box testing is centred around testing the software from an end-user's perspective, ensuring that all functionalities work as expected. Since only the external structure and design are to be tested, programming proficiency or knowledge about the working of the software's code is not required. 

Techniques like equivalence partitioning, boundary value analysis, and error guessing are commonly used to create test cases for conducting Black Box testing. Behavioural testing is primarily used at the functional level of software testing. 

Note: While Balck Box testing is user-friendly and effective in uncovering functional issues, it may not detect internal defects unrelated to functionality.

It would be best if you explored the What is Black Box Testing? Its Types and How To Do It article to learn more about Black Box testing. 

What is White Box Testing?

White Box testing, also known as clear, open, or glass box testing, delves into the internal structures and workings of the software. In lay terms, it is a software testing strategy in which a tester tests the implementation and impact of the code. The tester knows the software's internal workings, including its code, algorithms, and methods. 

The White Box testing approach is centred around verifying the internal code's correctness and efficiency. Testers must know programming languages, software architecture, and design patterns to conduct this type of testing. Methods like control flow testing, data flow testing, and statement coverage are utilized to conduct white box testing. This testing strategy is applied at the unit, integration, and system levels of software. 

Note: White Box Testing effectively identifies internal defects and optimizes code efficiency and maintainability. However, it requires programming expertise and can be more time-consuming than Black Box Testing.

It would be best if you explored the White Box Testing with Real Life Example article to learn more about White Box testing. 

Example of Black Box Testing vs White Box Testing 

Test Case: Testing a Calculator Application

Black Box Testing

• Scenario: Testers approach the calculator app as typical users without any insight into its programming or internal code structure.
• Process: They input various numbers and execute basic operations like addition, subtraction, multiplication, and division, checking for accurate outputs.
• Focus: The primary concern is the app's external aspects - its user interface elements (such as buttons and display) and overall functionality (ensuring that operations like '2+2=' result in '4').
• Techniques: Common strategies include equivalence partitioning, grouping similar input sets to predict consistent results, and boundary value analysis, focusing on extreme input cases (e.g., maximum number limits).
• Internal Knowledge Requirement: No understanding of the app's internal coding or algorithms is necessary. The tester's role is to validate the app's performance from an end-user perspective.

White Box Testing

• Scenario: Testers fully know the app's internal code, algorithms, and structure.
• Process: They delve into the app's source code, scrutinizing the accuracy and implementation of the underlying algorithms for each mathematical operation.
• Focus: The emphasis is on internal elements such as code efficiency (optimization and removal of redundant steps), correctness (ensuring the multiplication algorithm, for example, computes accurately), and logical integrity (identifying bugs within the code).
• Techniques: This involves advanced methods like control flow testing, examining the logical paths (such as conditional statements) in the code, and data flow testing, assessing how data is handled and manipulated within the app.
• Internal Knowledge Requirement: Profound knowledge in programming, software architecture, and design patterns is essential. The tester evaluates how the software is constructed and executed internally.

Key Differences Between White Box and Black Box Testing

• White box testing is time-consuming, where as Black box testing is fast.
• Black box testing provides less granular reporting, and white box testing provides more granular reporting.
• Black box testing does not require programming skills, while white box testing requires programming skills.
• White box testing focuses on code structure, conditions, paths, and branches. In contrast Black box testing focuses on the external or end-user perspective.
• Black box testing is done without knowing the program's structure or application, while white-box testing is done with the knowledge of the program's internal structure.

Conclusion

Black Box and White Box testing are two crucial methodologies in software testing, each serving distinct but complementary roles. With its focus on external functionality and user experience, Black Box testing is vital for ensuring that software applications meet user requirements and are user-friendly. On the other hand, White Box testing delves deep into the software's internal structure, playing a critical role in ensuring code efficiency, logic correctness, and overall software robustness.