Equivalence Partitioning is test case design strategies in black box testing. In this, the input data is divided into different equivalence data classes. This method is typically used to reduce the total number of test cases to a finite set of testable test cases, still covering maximum requirements.
In short, it is the process of taking all possible test cases and placing them into classes. One test value is picked from each class while testing.
In the equivalence-partitioning technique, we need to test only one condition from each partition/class.
This is because we can assume that all the conditions in that partition/class will be treated in the same way. If one condition in a partition/class works, we assume all of the conditions in that partition/class will work fine. Similarly, if one of the conditions in a partition/class does not work, then we assume that none of the conditions in that particular partition/class will work so again there is no mean to test all data in of that partition/class.
For Example :
An online store offers different discounts depending on the purchases made by the individual. In order to test functionality that calculates the discounts, we can identify the ranges of purchase values that earn the different discounts.
For example, if a purchase is in the range of $1 up to $10 has no discounts, a purchase over $10 and up to $100 has a 10% discount, and purchases of $101 and up to $500 have a 15% discounts, and purchases of $501 and above have a 30% discounts.