Black box testing is testing without knowledge of the internal workings of the item being tested. For example, when black box testing is applied to software engineering, the tester would only know the "legal" inputs and what the expected outputs should be, but not how the program actually arrives at those outputs.
A software testing technique whereby explicit knowledge of the internal workings of the item being tested are used to select the test data. Unlike black box testing, white box testing uses specific knowledge of programming code to examine outputs. The test is accurate only if the tester knows what the program is supposed to do. He or she can then see if the program diverges from its intended goal.
Black box testing maps a set of specific inputs to a set of expected outputs. An equivalence category is a collection of input sets. Two input sets belong to the same equivalence category if there is no reason to believe that if one works the other will not.
Therefore testing one input set essentially tests the entire category. .
Black Box Testing:.
1. Equivalence Partitioning - Because exhaustive black box testing is not feasible, black box test cases must be chosen to find different faults if possible. We can assume that similar inputs will result in similar responses, allowing the grouping of inputs into equivalence classes. In equivalence partitioning, only one or a few test cases are chosen to represent the entire equivalence classes.
Input data should be divided into equivalence classes based on consideration based of:-.
- valid vs invalid input values.
- valid vs invalid output values.
- similarity and difference of input values.
- similarity and difference of output values.
- similarity and difference of expected processing.
2. Boundary Value Analysis - Black box test cases must be chosen to maximize the chance of finding faults. Experience has shown that values at or near equivalence class boundaries are more likely to detect faults.