What is grey-box testing?

Grey-box testing is a software testing method that combines the black-box and white-box testing. In this case, the tester is not fully an "outside observer" of the system, but does not have full access to the source code. Instead, he designs and executes tests based on partial internal information, such as database structures, API documentation, system architecture or privilege levels.

The grey-box approach gives us the opportunity to take into account both user and administrative perspectives during testing. Access to the entry points and interfaces of the system under test allows for a more targeted detection of defects, be it functional mismatches or security risks.

Features of grey-box testing

• Understanding the application structure - Testers get a partial view of the inner workings of the application, even if the source code is not fully available to them.
• Identification of environment-related faults - Knowing how the system works can also reveal errors that only occur in certain contexts, such as privilege levels or data states.
• Combination of manual and automated tools - Both manual and automated testing methods can be used, making testing more flexible and efficient.
• Identifying practical and technical problems - It can identify both errors that affect the user experience and internal logical or data management problems.
• A bridge between developers and testers - Partial technical knowledge allows testers to communicate more effectively with developers, improving collaboration.

When is grey box testing recommended?

Grey-box testing is particularly useful in the following cases:

• During integration testing – When different modules or components need to be tested together, it allows you to check internal interfaces and data flows, ensuring that each part works seamlessly together.
• When testing web applications - For web systems where access to the internal structure is limited, it effectively detects vulnerabilities and functional errors.
• During safety assessments – With partial insider knowledge, testers can perform more targeted security testing to identify vulnerabilities more effectively.
• When testing distributed systems – When a system consists of multiple components communicating with each other, it helps to map the data flow and interactions between the components, thus increasing reliability.
• When checking business logic - The business processes of applications are often complex and critical. The grey-box approach allows a deeper examination of these without the need for full code-level knowledge, so that the internal workings and the expected outcome can be better compared.

The benefits of grey-box testing

• More comprehensive fault detection - With partial inside knowledge, testers are able to identify not only user errors, but also code-level or logic problems - covering a wider spectrum of bugs.
• Does not require deep programming knowledge - Testers don't need to know the full source code or have developer-level technical knowledge, so testing can be done with a lower technical entry threshold.
• Objectivity and independence - The testing remains impartial, as the tester examines the system as an outsider, but partially informed. This reduces the chance of potential conflicts with developers.
• A user-centred approach - Testing bridges the gap between development and end-user operation, so that the system can be optimised for real-world use.
• Time- and cost-effective - Since not all documentation and source code needs to be handed over, testing can be done faster while remaining sufficiently deep and focused.
•  More time for bug fixing - Faster detection of bugs allows developers to start fixing them at an early stage - reducing the cost and time of repairs.

The disadvantages of grey-box testing

Although grey-box testing offers many advantages, it is not ideal in all situations. 

• Restricted access to internal operations - The tester has only a partial knowledge of the internal architecture of the system, which can limit deeper, code-level testing. This can result in a lack of detail at the white-box level.
• Not suitable for deep testing of algorithms - It is not the most effective method for checking the operation of complex or critical algorithms, as the tester cannot fully see the logic or internal calculations.
• Difficult to design test cases – Because of partial knowledge, test case design can be complex: the tester has to balance information from "outside" and "inside" in a way that is both realistic and effective.
• Difficulties of error correlations - More complex systems, it can be difficult to determine exactly which component is the source of a failure. Partial insight is not always sufficient to identify the exact failure drivers.
• Not a substitute for full white-box testing - Since there is not full access to the source code, certain types of errors (e.g. hidden logic errors, memory management problems) may be missed in testing.

Grey-box testing techniques

When grey-box testing, several methods can be used depending on the type of errors you want to detect

Matrix Testing

This technique focuses on the business and technical risks associated with the variables defined in the application. Based on the frequency and importance of the factors identified by the developers, the most critical combinations are selected for greater attention during testing.

Pattern Testing

It builds on the analysis of past errors to identify the recurring patterns behind them. This allows the development of test cases that anticipate potential problems before the system is live.

Orthogonal testing (Orthogonal Array Testing)

This method is advantageous when few test cases are available but a large number of input combinations need to be covered. Orthogonal tables can be used to achieve the maximum possible coverage with minimum resources, especially for complex systems.

Regression Testing

Once the system has been modified, it ensures that new features or improvements do not impair existing functionality. It is an important part of quality assurance in continuous improvement.

State Transition Testing (STT)

This technique looks at the different states of the system and the transitions between them. It is essential to ensure that all possible state changes work correctly - for example, when logging in, making a payment, or changing privileges.

Decision Table Testing (DTT)

It can be used for complex business logic where there are multiple input conditions and associated output results. Decision tables help to organise and make transparent all possible combinations.

API Testing

In grey-box testing, the examination of the APIs - the public interfaces of the application - is of paramount importance. The goal is to ensure that the interfaces work as documented, respond appropriately to various inputs, and are reliable in their error handling.

Data Flow Testing (DFT)

Stream testing focuses on the movement and transformation of data in the system. The technique helps to detect problems such as uninitialized variables, incorrect data manipulation or improper data storage.