Equivalence Partitioning is a software testing technique used to reduce the number of test cases by dividing the input data into partitions or groups, where each group is expected to behave similarly. The principle is that if a test case works for one value in a partition, it will likely work for other values in the same partition. This technique helps identify a representative sample of test cases that can cover a wide range of inputs efficiently.
Key components of equivalence partitioning include:
- Input Partitioning: The input domain is divided into several equivalent classes, each representing a range of valid or invalid input values. These classes are treated as if they are likely to produce the same result.
- Valid Equivalence Class: A set of valid inputs that the system should accept, such as valid dates, email formats, or positive integers.
- Invalid Equivalence Class: A set of invalid inputs that the system should reject, such as incorrect date formats, negative numbers where only positive are expected, or alphanumeric values in numeric fields.
- Representative Test Cases: One test case is chosen from each equivalence class to represent the entire class, reducing the number of test cases required while maintaining broad coverage.
- Boundary Values: Equivalence partitioning often pairs with boundary value analysis, testing the edges of the equivalence classes to ensure that the system handles extreme values correctly.
Equivalence partitioning helps optimize testing by reducing redundancy, ensuring that all types of input are covered without having to test every possible input individually.