Among the various types of testing, there are “black box” testing and “white box” testing. The former checks the application's functionality without knowledge of its internal workings, such as studying the code, etc. In contrast, the latter involves a thorough examination of the software, diving deep into how the application operates internally. However, there are situations where an in-depth analysis of the software's inner workings is impractical or impossible. This is where a third, intermediate option — gray box testing — comes into play.
In this article, we will explore what gray box testing is, the different methods involved, how to conduct it, as well as the advantages and disadvantages of this type of testing.
What is gray box testing?
Gray box testing (also known as grey box testing) is a software testing method that combines elements of both black box and white box testing. In this approach, the tester has some understanding of the internal workings of the application, enabling them to identify defects that might not be apparent during black box testing, while still viewing the application from an external perspective.
The name of this testing type suggests that the tester sees the program as a translucent box, partially aware of its contents. They may know the components it consists of but not how everything works together. This perspective aligns with how attackers and average users perceive the application. Therefore, gray box testing not only evaluates the functionality of the software but also assesses its security.
Gray box testing is an integral part of the software development life cycle and is conducted during the testing phase. It is crucial for understanding the internal mechanisms and verifying the functionality and performance of the software application. Additionally, it is used to identify bugs that are challenging to uncover through black box testing.
Gray box testing contributes to a comprehensive and effective evaluation process by using both the developer's knowledge and the tester's perspective, ensuring the quality and reliability of the software.
Objectives of gray box testing
Gray box testing is particularly effective in scenarios where both the system's functionality and its internal operations — such as seamless integration of components — are of interest.
Gray box testing allows for:
- Combining the advantages of black box and white box testing, enabling testers to view the product from an ordinary user's perspective while also having the knowledge of a developer. It provides a balanced, semi-transparent view of the application.
- Optimizing the testing process by reducing redundant testing through the use of both black box and white box methods to save time and resources.
- Bridging the gap between developers and testers by fostering collaboration and promoting a shared understanding of the software's internal workings and user experience.
- Improving overall product quality by identifying a wider range of errors, including logical mistakes, data manipulation issues, and security vulnerabilities.
- Reducing costs associated with prolonged functional and non-functional testing.
Gray box testing techniques
Gray box testing incorporates several testing techniques.
Matrix testing
In matrix testing, business and technical risks are evaluated. Developers identify all the variables present in the program, each of which has associated risks. A specialized risk matrix is created to prioritize test cases based on their severity and potential impact.
Distinct elements and combinations are identified. Elements can include specific functions, components, and aspects of the application, such as user authentication, product search modules, payment system integration, and data caching mechanisms.
A combination refers to sets of input values or parameters of the software. For example, in the user authentication function, possible combinations include "correct username + correct password" and "correct username + incorrect password." For the product search module, combinations might be "existing product name + available quantity" or "search by SKU + price filter," among others.
Each element or combination of input data and application parameters is assigned a score in the risk matrix. This score indicates the level of risk associated with the elements and combinations, allowing testers to prioritize their testing efforts by focusing on elements with high scores. Such an approach ensures that the most critical issues are addressed first, thereby reducing risks to the software.
Pattern testing
This technique involves analyzing previous defects and determining the root cause of failures by studying the code. Based on the insights gained, new tests are designed to verify programs similar to those where issues were identified. This proactive approach helps detect defects before they reach production. Examples of patterns targeted by this testing include loops, conditions, function calls, and data structures.
For instance, suppose a vulnerability is discovered in the registration form of an online store: the lack of validation for SQL injections in the email input field. Code analysis reveals a pattern of directly inserting user input into SQL queries without prior sanitization. Testers then create a suite of tests with various SQL injection scenarios to assess the security of user input. These tests are applied to all forms on the site, including login, product search, and order processing. As a result, similar vulnerabilities are identified and resolved in other areas of the web application, significantly enhancing its overall security.
Orthogonal array testing
This is a method of statistical testing that can be useful when maximum coverage is required, especially when there are very few test cases but a large amount of test data. This is particularly relevant for testing complex applications.
This testing technique encompasses all possible combinations of input parameters and variables by developing corresponding test cases. It employs orthogonal arrays to identify the variables/input parameters that have the most significant impact on the functioning of software applications.
The main advantage of this method is the ability to create test cases that account for all variables and input parameters without executing a large number of tests. As a result, maximum test coverage is achieved while minimizing the time and effort required for execution.
Regression testing
Regression testing is the process of testing software after each modification to ensure that changes or new features have not broken anything in the system. It is also conducted after fixing previously identified defects to verify that the fix has not affected other functionalities of the software.
Within gray box testing, regression testing helps identify any potential defects related to changes made to a part of the software application.
This technique allows for the early detection of errors during the gray box testing phase, before they can cause issues in the software development process.
State transition testing
State transition testing is applied to systems that exhibit different states during operation. Its purpose is to ensure that transitions between states are handled correctly and that the system behaves as expected in all possible states and transitions.
For example, suppose you are developing a music player that can have the following states:
- Stopped
- Playing
- Paused
- Loading track
- Playback error
During state transition testing, you would verify that each transition between states occurs correctly, the interface updates accordingly, and the player’s functionality operates as expected in each state.
Boundary value analysis
The boundary value analysis method checks whether input data falls within a specified range of values. When any value outside this range is entered, the system generates error messages.
This technique includes testing at internal boundaries and external boundaries. In the first case, values within the range should yield a positive result. In the second case, values outside the range should be tested. A test fails if the system incorrectly processes values at the boundaries or beyond the acceptable range.
For example, suppose you have a form on your website for entering a user's age, with an acceptable range from 18 to 99 years. The test cases for boundary value analysis would be as follows:
Internal boundaries:
- Input 18 (lower boundary) – should be accepted
- Input 19 (just above the lower boundary) – should be accepted
- Input 98 (just below the upper boundary) – should be accepted
- Input 99 (upper boundary) – should be accepted
External boundaries:
- Input 17 (just below the lower boundary) – should be rejected
- Input 100 (just above the upper boundary) – should be rejected
Additional tests:
- Input non-numeric values (e.g., “abc”) – should be rejected
- Input negative numbers – should be rejected
Decision table testing
This method involves testers creating tables that display various combinations of input conditions and their corresponding actions or outcomes. Decision tables are used to generate test cases that cover multiple possible scenarios, helping to ensure test completeness and identify potential logic errors in the program.
For example, suppose you are implementing a discount system in your online store.
Conditions:
- Customer registered (Yes/No)
- Purchase amount greater than $100 (Yes/No)
Actions:
- A. Apply a 5% discount
- B. Apply a 10% discount
- C. Do not apply a discount
Decision table:
| Aspect | Sanity testing | Regression testing |
|---|---|---|
| Subset of regression | Yes | No |
| Purpose | Checks new functionality or code changes | Checks all areas affected by changes |
| Relationship | Part of regression testing | Independent testing |
| Execution sequence | Before regression testing, after smoke testing | Typically after sanity testing |
| Automation | Often done manually | Usually automated |
| Test scope | Surface-level testing | Not considered surface-level testing |
| Test coverage | Focuses on specific functionality | Extensive, covers most or all functionality |
| Use of scripts | Does not use scripts | Uses scripts |
| Test execution | Full test cases not executed | Full set of test cases created |
| Depth of testing | Superficial and broad | Extensive and deep |
How to perform gray box testing
The use of gray box testing depends on the requirements of the software application, the testing objectives, level, scope, tasks, and tools. It can be conducted in the following situations:
- When testing interactions between various components of the software application.
- After each change or update to the system.
- To assess the security of software applications by simulating hacking attacks.
- To verify the functionality of databases by checking data schemas, data flows, and constraints.
- When testing APIs to evaluate their functionality and interaction with the software applications that utilize them.
Gray box testing does not require developing test cases from the source code. In this case, knowledge of the architecture, algorithms, internal states, or other high-level descriptions of the program's behavior is sufficient for creating test cases. All basic black box testing techniques can be employed for functional testing.
To perform gray box testing, certain steps should be followed:
- Compile a list of all input data obtained from black box and white box testing methods. Inputs can come from various sources, including user interactions, network requests, or automated test scripts.
- Compile a list of all expected output data dependent on the input data. For example, in the case of a banking application, the input could be a user's command to transfer funds. Expected outputs might include successful completion of the transfer and transaction confirmation, a message indicating the inability to transfer with explanations, and error messages from the application.
- Create a list of all key paths or routes the software application will take during testing. These can be determined by analyzing the architecture and design of the software application or its expected functionalities.
- Identify sub-functions for more in-depth testing. Sub-functions are specific parts or components of the application that require closer attention. Typically, the prioritization of these sub-functions is based on their importance and criticality to the overall functionality of the application.
- Once sub-functions have been identified, compile a list of all input data that can be used to test each sub-function. These inputs can be derived from black box and white box testing.
- Create a list of all expected outputs for each sub-function.
- Develop test cases or test each sub-function individually. Each test case should be executed with the specified input values and verified for conformity between the actual and expected results.
- Analyze the results obtained and ensure that the sub-function operates as intended. If defects are discovered, take steps to address them.
Advantages of gray box testing
Gray box testing offers several advantage, such as:
Holistic perspective: By combining the viewpoints of the user (black box testing) and the developer (white box testing, gray box testing provides a more comprehensive evaluation of the system. You can test the software application from the user’s perspective while also understanding its internal workings.
Security assurance: Gray box testing is particularly effective for identifying security vulnerabilities, as it examines both external and internal aspects of the system.
Cost-effectiveness: It does not require testers to have deep programming knowledge, making it more economical since less experienced testers can be hired.
Dual advantage: The combination of black box and white box testing methods leverages the strengths of both approaches. Testers can delve into the code when necessary while also assessing the application’s functionality from the end user's perspective.
Limitations of gray box testing
Difficulty in tracking defects: In distributed systems with components located in different places, it can be challenging to trace a defect back to its source. This is because testers do not have a complete understanding of the internal workings of the application’s components. For instance, a defect in one component may affect the functionality of other components, but if the tester lacks access to the source code of the first component, they may be unable to identify the root cause of the issue. Consequently, some defects may go undetected for this reason.
Challenges in creating test cases: Again, with limited knowledge of the internal structure and interactions of the application’s components, testers may find it difficult to create adequate test cases.
The balanced advantage of gray box testing
Gray box testing represents a balanced approach to ensuring software quality, allowing testers to combine the external perspective of the user with a partial understanding of the system’s internal workings. It is an essential tool in software quality assurance that plays a key role in modern software development processes.
Due to its flexibility and effectiveness, gray box testing enables development and testing teams to collaborate more effectively, resulting in the creation of more reliable and high-quality products. It is particularly valuable for identifying security issues and optimizing performance, which may be overlooked when using only black-box or white-box methods.
Despite some limitations, the advantages of gray box testing significantly outweigh its drawbacks. It not only enhances the overall quality of software but also fosters a deeper understanding of the system among all participants in the development process, ultimately leading to the creation of more sophisticated and user-centered software products while reducing testing costs.
