What is the technique of equivalence class analysis and how is it applied in software testing?
sobes.tech AI
Answer from AI
The Equivalence Partitioning technique is a test case design method based on dividing input data (or output conditions) into classes, where representatives of these classes are processed similarly by the program. Testing one representative from each class is considered sufficient to cover the entire class.
Main idea: If a test on one class representative reveals an error, then a test on any other representative of the same class is likely to reveal the error as well. If a test on one representative does not reveal an error, then a test on any other representative of the same class is also likely not to reveal an error.
Application:
- Identification of equivalence classes:
- Determine valid and invalid classes for each input field (numeric range, set of strings, boolean values, etc.).
- For numeric ranges:
- Valid range.
- Numbers less than the lower bound (invalid class).
- Numbers greater than the upper bound (invalid class).
- For sets of values:
- Valid values.
- Invalid values (e.g., strings in a numeric field).
- For example, for the "Age" field from 18 to 65:
- Valid class: 18-65 (e.g., 25, 40, 60)
- Invalid class: < 18 (e.g., 17, 0)
- Invalid class: > 65 (e.g., 66, 100)
- Creating test cases:
- Select one representative from each identified class (valid and invalid).
- Create test cases with the selected representatives as input data.
Example:
Order form, "Quantity of goods" field, valid value from 1 to 99.
| Equivalence Class | Type | Test Representatives |
|---|---|---|
| Less than 1 | Invalid | 0, -5 |
| From 1 to 99 | Valid | 1, 50, 99 |
| More than 99 | Invalid | 100, 1000 |
| Non-numeric values | Invalid | "abc", " " |
At least one representative from each class is chosen to create a test case. For example, this field will have at least 4-6 test cases covering all identified classes.
Advantages:
- Reduces redundancy of test cases.
- Helps systematize the testing process.
- Ensures good test coverage with fewer tests compared to testing every possible input value.
Disadvantages:
- May not detect errors at boundary values (often used in combination with boundary value analysis).
- Effectiveness depends on correct identification of equivalence classes.