Black Box Testing, also known as Behavioral Testing, is a software testing method in which the internal structure/design/implementation of the item being tested is not known to the tester. These tests can be functional or non-functional, though usually functional.
This method is named so because the software program, in the eyes of the tester, is like a black box; inside which one cannot see.
Black Box Testing is contrasted with White Box Testing. View Differences between Black Box Testing and White Box Testing.
This method of attempts to find errors in the following categories:
- Incorrect or missing functions
- Interface errors
- Errors in data structures or external database access
- Behavior or performance errors
- Initialization and termination errors
A tester, without knowledge of the internal structures of a website, tests the web pages by using a browser; providing inputs (clicks, keystrokes) and verifying the outputs against the expected outcome.
Black box testing occurs throughout the software development and Testing life cycle i.e in Unit, Integration, System, Acceptance and regression testing stages.
Tools used for Black Box testing:
Black box testing tools are mainly record and playback tools. These tools are used for regression testing that to check whether new build has created any bug in previous working application functionality. These record and playback tools records test cases in the form of some scripts like TSL, VB script, Java script, Perl.
Advantages of Black Box Testing
– Tester can be non-technical.
– Used to verify contradictions in actual system and the specifications.
– Test cases can be designed as soon as the functional specifications are complete
Disadvantages of Black Box Testing
– The test inputs needs to be from large sample space.
– It is difficult to identify all possible inputs in limited testing time. So writing test cases is slow and difficult
– Chances of having unidentified paths during this testing
Methods of Black box Testing:
Graph Based Testing Methods:
Each and every application is build up of some objects. All such objects are identified and graph is prepared. From this object graph each object relationship is identified and test cases written accordingly to discover the errors.
This is purely based on previous experience and judgment of tester. Error Guessing is the art of guessing where errors can be hidden. For this technique there are no specific tools, writing the test cases that cover all the application paths.
Boundary Value Analysis:
Many systems have tendency to fail on boundary. So testing boundry values of application is important. Boundary Value Analysis (BVA) is a test Functional Testing technique where the extreme boundary values are chosen. Boundary values include maximum, minimum, just inside/outside boundaries, typical values, and error values.
Extends equivalence partitioning
Test both sides of each boundary
Look at output boundaries for test cases too
Test min, min-1, max, max+1, typical values
1. Number of variables
For n variables: BVA yields 4n + 1 test cases.
2. Kinds of ranges
Generalizing ranges depends on the nature or type of variables
Advantages of Boundary Value Analysis
1. Robustness Testing – Boundary Value Analysis plus values that go beyond the limits
2. Min – 1, Min, Min +1, Nom, Max -1, Max, Max +1
3. Forces attention to exception handling
Limitations of Boundary Value Analysis
Boundary value testing is efficient only for variables of fixed values i.e boundary.
Equivalence partitioning is a black box testing method that divides the input domain of a program into classes of data from which test cases can be derived.
How is this partitioning performed while testing:
1. If an input condition specifies a range, one valid and one two invalid classes are defined.
2. If an input condition requires a specific value, one valid and two invalid equivalence classes are defined.
3. If an input condition specifies a member of a set, one valid and one invalid equivalence class is defined.
4. If an input condition is Boolean, one valid and one invalid class is defined.
Different independent versions of same software are used to compare to each other for testing in this method.