In software testing and QA, there are so many extraordinary terms, like black-box and white-box testing, monkey testing or gorilla testing. Let’s stick to the first two testing types: black-box and white-box and figure out their distinctive features, advantages, and downsides, as well as the use cases.
To begin with, poorly organized quality assurance is one of the proven ways to destroy app reputation in addition to the software vendor’s reputation. Black-box and white-box tests are basic approaches to detect software drawbacks and fix them up on time.
What is black-box testing all about?
Black-box testing (BBT) is the same as behavioral, data-driven or functional testing. It is a software testing approach for reviewing and testing the app structure, design, and overall functionality.
Knowing nothing about the app internal structure, test engineers select valid and invalid inputs to check if the output is correct. They simulate the behavior of an ordinary user by entering data in fields, filling out forms or enabling certain features.
Black-box testing is based on trial and error. It means, the decision if the app passes or fails the test is based on the app usability and proper performance, and not on the code quality or internal characteristics.
Think of this testing type as of a TV set: as a user, you don’t have to understand the nitty-gritty of the system. You just want to switch it on and off, change channels, apply certain settings with the help of the remote control. The TV is the application under test. The user interface is presented by the TV set interface and the remote control buttons. The specifications tell you to check the way it works.
Black-box testing methods
There are several of them, but each one is focused on testing inputs. The significance of the inputs cannot be overestimated during the BBT. Therefore, each method considers inputs in its own way. Here are a couple of methods used in black-box testing.
Equivalence Partitioning splits the massive sets of potential inputs into more specific classes for equivalent treatment. With its help testers can identify the specific set of functions with input data and output results. The characteristics of these functions help to create test data.
Example of Equivalence Partitioning: the field permits only numeric characters, at the same time, the length is 6-14 characters. The equivalence classes would be: A-Z letters entered in the field make it invalid. Numeric characters are valid. The input length from one to five characters and 7+ characters is invalid. The input of 6-14 characters is valid.
Boundary Value Analysis has the following goal: it selects the extreme input values which lead to errors in order to narrow down the possible test cases. Boundaries help to adjust the field and help users enter the correct data. This way, the primary task of software testing teams is to detect input value boundaries to decrease the number of test cases. The technique can be used for variables with solely fixed values only.
Example of Boundary Value Analysis: to get a 25% discount coupon for the next in-app purchase, the amount of the purchase should range between $50 and $100. Low boundary +/- one ($49 and $51), on the boundary ($50 and $100), upper boundary +/- one ($99 and $101).
Cause-Effect Graphing is widely used in the case of multi-choice input types. Graphs help to identify input values, leading to errors.
Example of cause-effect graphing: If A is true and B is false, then C is true. If the customer owns a bonus card and makes no purchase this month, then they get 5 bonuses.
If A is false and B is true, then C is true. If the customer doesn’t have a bonus card, makes a purchase this month (and receives such a cared), they get 5 bonuses afterward.
If A is false and B is false, then C is false. Without having a bonus card and without making a purchase, the customer gets no bonuses.
Error guessing is an unstructured method based on previous experience in writing tests. The testing engineer detects problematic issues in the app by applying statistical data, general knowledge, specific knowledge about the module, and their personal logical conclusions. In order to run error guessing effectively, you need a team of skilled and talented analysts.
Example of error guessing: the analyst considers the checkout page error-prone and creates the task of creating detailed test cases revolving around the possible issues with the checkout page. Different data combinations are used for that.
Other methods of black-box testing include:
- Decision table testing
- All-pairs testing
- State transition testing
- Use case testing
- User story testing
- Domain analysis
- Syntax testing.
Here are the advantages of BBT (black-box testing):
- Fast test case development – in the case of black-box testing, the app’s GUI is the only aspect to consider, so there is no need to master or even understand code.
- Clear separation between the technical and user’s perspectives – testers act like users trying to reveal product flaws and test the UX offering an unbiased review.
- Applicable for large parts of code – unlike white-box testing.
Here are a few shortcomings of BBT:
- Incomplete coverage – test paths can be missed or tested several times while only a part of test scenarios is executed. However, the significance of this drawback depends on the project details.
- Low-efficiency testing when used separately – it’s impossible to test all app aspects solely by black-box testing, as it doesn’t provide deep testing of certain functions and features.
- It requires clear test specifications – the high-quality outcome is impossible if the testing specialists don’t have a clear idea about things they need to test.
If the development is driven and powered by testing, the black-box testing includes some acceptance criteria. They are later transformed into the list of functions for further development. In such cases, black-box testing is linked to the automation process, for example, behavior-driven software development.
What is white-box testing?
White-box testing can be interchangeably used with clear- or glass-box testing, as well as transparent box testing or structural testing. Unlike black-box testing, in this type of quality assurance, the testers know enough about the code of the Application Under Test and implement this knowledge. For example, when configured correctly, white-box tests can reveal poorly defined variables or wrong call functions. The white-box testing deals with the software from its internal perspective, thus, it requires certain programming competencies.
Software developers can automate white-box testing to deal with defect parts of code to reduce the chance for errors later in the development process. Basically, white-box testers are software engineers, because even with the top automation tools, white-box testing is an exhausting and sophisticated task. What’s more, test automation may appear to be useless if the app’s codebase frequently and substantially changes.
You can think of the white-box testing as of the interaction between a car and a car mechanic. A car is the AUT (application under test). The mechanic willing to repair the engine is the white-box tester. By the way, the car driver is a black-box tester in this example.
White-box testing methods
- Statement Coverage – when it is complete 100% then all statements in the app are executed at least once.
- Branch Coverage – the testing method verifies that every branch is executed at least once.
- Decision Coverage – full decision coverage implies that all decision directions are executed at least once.
- Condition Coverage – in the case of condition coverage, each decision with all of the possible outcomes is executed at least once.
- Decision/Condition Coverage – 100% decision/condition coverage means that all possible variations of conditions and outcomes are executed at least once.
- Path Coverage – this testing method ensures all of the paths described by the app are executed at least once.
- Multiple Condition Coverage – each entry point is used at least once during testing.
Software engineers select the combination of multiple techniques depending on the app peculiarities while using them all can lead to the extra-large number of test cases to be executed.
In most cases, white-box testing is automated and is carried out in the form of unit tests. When implemented before the development stage, it is executed as the Test-Driven Development (TDD).
Here are the advantages of WBT (white-box testing):
- Rapid problem identification – testers implement unit tests to work with smaller parts of the source code and locate defects at the early development stage.
- Facilitated programming – testers can sift through the parts of codes prone to errors and save developers a lot of time later.
- Security issues detection – experienced white-box testers can simulate attacks at the app’s code to effectively expose security risks and drawbacks.
Here are a few shortcomings of the white-box testing:
- Prone to human errors – like other manual testing types, there may be issues with white-box testing.
- Organizational difficulties – there is little chance to find testers with enough expertise to perform white-box testing.
- Financial expenses – this reason is interconnected with the previously mentioned one: qualified testers are expensive to hire.
Black-box testing vs white-box testing: when it’s better to use BBT and when you’d rather choose WBT?
White-box testing is perfect when it can be carried out by the developers who created the code with the help of unit tests. This is especially true for smaller teams and smaller-scale projects because of the limited number of testers.
White-box testing types, like path testing, loop testing or condition testing, don’t require the complete GUI. Therefore, WBT is a great option to test early app builds and a rational choice for development to verify small program parts in-house. It is an effective way to test every path. As far as the drawbacks are concerned, white-box testing methods ensure the code is good but provides no guarantees this code is able to generate what users eventually expect. Also, it doesn’t separate the app from the testing environment, which may sometimes break the source code and add tasks for the developers.
The closer you are to the release date, the higher the priority of the black-box testing is.
Black-box testing, for example, functional, non-functional or regression testing, is a widespread testing option and is what most testers actually do. The testing is based on prioritization: how important this function is for the ready product. Its main goal is to test the behavior of the software, not the internal operation of the system. A large team of testers can identify UX problems last minute before the release. Test cases are easy to generate, while the dev team quickly responds to detected drawbacks. However, it is important to carefully organize black-box testing scenarios.
The well-thought-out combination of BBT and WBT gives software development companies the best chance to improve the end-user experience by creating a full-functioning end product.
To sum it all up:
- Black-box testing can’t replace white-box testing and vice versa. QA engineers usually implement a combination of them at the various development cycle phases in order to address different types of errors.
- For example, white-box testing may not require a working user interface, therefore, it is suitable for early testing. It requires sufficient programming skills and may include test automation.
- Black-box testing is great for pre-release testing, which ensures the app works exactly as intended from the user’s perspective.
- Each software development and QA team selects its own successful proportion between the white-box and black-box testing methods.
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