Black box testing is a software testing approach in which the functionality of the SUT (Software Under Test) is tested without regard for its implementation specifics, internal route knowledge, or internal code structure.
This type of testing is entirely dependent on the software's specs and needs.
The outputs and inputs of the software system, rather than the program's underlying knowledge, are the focus of black-box testing.
The "black box" is the system that undergoes this form of testing, and it may be any program, such as a database, website, or operating system.
Black box testing examines the system's comprehensive functioning as well as its behavior.
This technique of testing is also known as behavioral testing or functional testing.
During the phases of the software testing life cycle, such as regression testing, acceptance, unit, system, integration, and software development, this testing approach is crucial.
End-users who want to do software verification may benefit from black box testing approaches.
The methodologies used during Black box testing for a software program are as follows.
It is one of the most important and helpful Black box testing techniques for equivalence partitioning. BVA may be used to evaluate any program that has a boundary or extreme values.
Rather than concentrating on the range of input values, this approach is capable of discovering problems in the limitations of input values. Edge or extreme output values are likewise dealt with via boundary value analysis.
Black box testing is a method for writing test cases that is frequently utilized. It may be beneficial for condensing a large number of potential inputs into a smaller number of more effective ones.
It is accomplished by categorizing inputs into classes and assigning a value to each class.
It's used when you need to do a lot of testing and you don't want your inputs to be redundant.
This method generally examines a system's status, outputs, and inputs throughout a period of time.
It tests for behavioral changes of a system in a certain state or another state while keeping the same inputs, depending on the kind of software being tested.
The test cases for this approach are built by examining the order in which the inputs transition and state or events occur.
The predicted output values and all states will be traversed over the whole collection of test cases.
|Condition||Rule 1||Rule 2||Rule 3||Rule 4|
|End of Month||No||Yes||Yes||Yes|
In certain cases, the input combinations for monitoring several options may get rather difficult.
Decision tables are used in such complicated scenarios because they provide testers with an orderly perspective of the inputs and anticipated outcome.
This method is quite similar to graph-based testing, with the exception that tables are used instead of diagrams or graphs.
A graph is drawn to demonstrate the relationship between the causes (inputs) and the effects (outputs) that trigger the effects in this Black box testing approach.
This testing makes use of a variety of output and input combinations. It's a useful tool for understanding the software's functional performance since it vividly depicts the flow of inputs and outputs.
This testing method is capable of predicting erroneous outputs and inputs, allowing the tester to quickly correct the problem. It is totally reliant on the end user's judgment and impression of the previous experience.
There are a few other common approaches of this testing, such as the fuzzing technique, all pair testing, and orthogonal array testing, in addition to the ones mentioned above.
The example below demonstrates how these testing methodologies may be used to evaluate particular software with supplied inputs.
When thinking about a buying situation,
If you spend $500, you'll get a 5% discount.
If you spend $1000, you'll get a 7% discount.
If you spend $1500 or more, you'll get a 10% discount.
It is feasible to split inputs into four divisions using the Equivalence partitioning approach of this testing, with amounts less than 0, 0 – 500, 501 – 1000, 1001 – 1500, and so on. This testing approach will not take into account variables such as the maximum shopping limit or product specifications.
The boundary values will be 0, 500, 501, 1000, 1001, and 1500 when boundary values are added to the partitions. The lowest and higher values are normally evaluated using the BVA approach, therefore numbers like -1, 1 and 499 will be included. Such values will aid in the explanation of software input value behavior.
When a shopper spends more than $1500 twice in a month, their status is moved from Gold to Platinum, and if he does not shop for the following two months, his position is returned to Gold, according to the State Transition Testing approach of Black box testing. The tester may achieve such a complicated track by using additional test cases.
Regression testing, unit testing, beta testing, integration testing, system testing, functional testing, load testing, and other processes are divided into distinct categories. However, the most common varieties are described here.
Functional Testing (FT) − This sort of testing aids testers in determining a software's or system's functional requirements.
Testing for Regression − This sort of testing is done after a system maintenance operation, upgrades, or code patches to see how the new code compares to the old code.
Non-Functional Testing (NFT) − This sort of testing is unrelated to functional testing and instead focuses on non-functional factors such as usability, scalability, and performance.
The following table highlights the differences between Black Box Testing and White Box Testing −
|Black Box Testing||White Box Testing|
|Used to evaluate the software without understanding how it works on the inside.||Executed after understanding the software's fundamental structure.|
|Testers are in charge of this.||Developers worked on it.|
|It is not necessary to know how to program.||Knowledge of programming is required.|
|Implementation expertise is required.||It is not necessary to have any prior experience with implementation.|
|Testing at the next level||Testing at a lower level|
|It takes less time.||It takes a lot of time.|
|Done by trial and error.||It is possible to test data domains and
|Black box testing comes in a variety of
shapes and sizes.||White box testing comes in a variety of
shapes and sizes.|
|Not appropriate for testing algorithms||Appropriate for algorithm testing|
Black Box testing levels may be used in a variety of situations −
The specifications and requirements will be analyzed.
The system will be given both positive and negative inputs in order to validate it.
The tests' outputs will be specified ahead of time.
The test cases will be carried out.
The actual and anticipated outputs will be compared.
The issues that have been fixed will be retested.
For functional and regression testing, use QTP with Selenium.
Non-functional testing using LoadRunner and Jmeter
In general, following a methodical procedure to test a project/application maintains quality and is valuable in the long term for subsequent rounds of testing.
The first step is to comprehend the application's requirement statement. There should be a well-documented SRS (Software Requirement Specification) in place.
Sets of valid and invalid inputs with their intended outputs are determined using the previously described Black Box Testing methodologies such as Boundary Value Analysis, Equivalence partitioning, and so on, and test cases are built based on that.
The intended test cases are run to see whether they pass or fail, and the actual outcomes are compared to the predicted ones.
Failed test cases are reported as Defects/Bugs to the development team, who will fix them.
In addition, the tester retests the problems after they have been repaired to see whether they are still there.
A technical background is not required of the tester. It's critical to test by putting yourself in the user's shoes and thinking from their perspective.
Once the project/application has been completed, testing may begin. Both testers and developers operate in their own area, without intruding on each other.
For big and sophisticated applications, it is more effective.
Defects and inconsistencies may be detected early in the testing process.
There is a risk of neglecting the probable circumstances of the scenario to be examined if you don't have any technical or programming experience.
It is feasible to test fewer inputs and outputs in a given amount of time by bypassing all available inputs and output testing.
For big and complicated projects, complete test coverage is impossible.