Equivalence Partitioning, also known as Equivalence Class Testing, is a powerful black-box testing technique designed to streamline testing by minimizing the number of test cases while ensuring comprehensive coverage.
This approach is widely used to make testing more efficient without sacrificing effectiveness. Let’s learn more about how it’s done!
Equivalence Class Testing is a black-box testing method where testers categorize input data into equivalence classes (or partitions). Each of these classes contain values that should be treated in the same way by the system.
Testers then select one or more representative values from each equivalence class for testing. Since these values should yield the same result as any other input in the class, this approach significantly reduces the need to test every possible input.
Equivalence partitioning is designed to minimize the number of test cases while maintaining thorough coverage.
Reduced Test Volume: By grouping input values into equivalence classes, you can drastically cut down the number of test cases while still covering all logical conditions.
Systematic Coverage: It provides a structured way to ensure every input domain (valid and invalid) is tested, rather than relying on ad-hoc test selection.
Improved Efficiency: Testers spend less time designing and executing redundant tests since each class represents a broad range of behavior.
Early Defect Detection: Invalid equivalence classes highlight boundary and error conditions early, which can uncover defects sooner in the cycle.
Easy to Combine With Other Techniques: It works well alongside boundary value analysis or decision tables to deepen coverage of high-risk or edge conditions.
Requires Deep Domain Knowledge: Defining correct equivalence classes demands a good understanding of the system’s input domains, rules, and constraints.
Risk of Missing Edge Cases: If classes are defined too broadly or incorrectly, subtle edge cases may never be tested.
Not Sufficient for Complex Logic: For systems with intricate state changes, interactions, or temporal behavior, equivalence partitioning alone may not expose all defects.
Maintenance Overhead: When requirements or data ranges change, the equivalence classes and their test cases must be re-evaluated and updated.
False Sense of Completeness: Teams may believe they’ve achieved full coverage just because all classes are tested, while real-world usage might include combinations not represented.
Typically, testers categorize values into two primary classes:
These are input ranges or sets that the system should accept and process correctly because they comply with the defined requirements.
Here are several examples of valid equivalence classes:
A password field requires 8–20 characters: a valid class is any string between 8 and 20 characters (e.g., “Pa55word!”, “LongerPass123”).
An age field accepts 18–65: a valid class is all numbers 18–65 (e.g., 25, 45).
Testing one representative from each valid class gives confidence that the system behaves correctly for all inputs in that class.
These are input ranges or sets that the system should reject or handle differently, because they violate the defined requirements.
Here are several examples of invalid equivalence classes:
A password field requires 8–20 characters: an invalid class is any string with fewer than 8 characters (e.g., “short”) or more than 20 characters (e.g., “thispasswordistoolongandshouldfail”).
An age field accepts 18–65: an invalid class is all numbers below 18 (e.g., 15), above 65 (e.g., 80), or non-numeric input (“abc”).
Testing one representative from each invalid class verifies that the system correctly blocks, sanitizes, or errors on disallowed inputs.
To illustrate how equivalence class testing works, let's use a simple example. Suppose you're testing a function that validates a user's age for an online registration form, with a valid age range of 18 to 60 years.
Here’s how you could create equivalence classes:
Now, let's select representative values from each class:
From these, we can generate the following test cases:
To ensure you're creating effective equivalence classes, follow these key principles:
By adhering to these rules, you can reduce the number of test cases without compromising quality. While you may choose to create additional test cases, they usually won't uncover new issues. The main goal is to ensure broad test coverage while keeping the process manageable.
Although equivalence partitioning is efficient, there's always a risk of missing edge cases. For example, imagine the developers added a condition like:
if (age == "30")
then REJECT
This type of unexpected behavior could slip through unless you have access to the source code or receive specific guidance from the developers.
When inputs have clear ranges or categories
Example: An age field accepts 18–65. Make one valid class (18–65) and two invalid classes (<18, >65).
When the system behaves uniformly across a range
Example: Shipping cost is the same for 0–5 kg packages. One test at 3 kg covers that class.
When you need to reduce redundant tests without losing coverage
Example: A form accepts 1–1000. Test one or two representatives from each partition rather than every number.
When designing tests early from requirements or API specs
Example: An API returns 200–299 for success, 400–499 for client errors. Partition by status code ranges to plan tests.
When pairing with boundary value analysis for edge coverage
Example: A password field accepts 8–20 characters. Equivalence classes cover “valid,” “too short,” and “too long,” and boundary tests hit exactly 7, 8, 20, and 21 characters.
Here are some scenarios where equivalence partitioning works well:
Equivalence Partitioning is a valuable testing technique that helps testers reduce the number of test cases without sacrificing quality.
Equivalence Class Partitioning (ECP) is a black-box testing technique that divides input data into groups (or partitions) with similar behavior. It is used to reduce the number of test cases while maintaining adequate coverage by testing one value from each group instead of testing all possible inputs.
To identify equivalence classes:
ECP focuses on grouping inputs into equivalent partitions, while BVA targets the values at the edges of these partitions. For example, if a valid input range is 1-100, ECP tests a representative value from the range, while BVA tests the edge values like 1 and 100.
Yes, ECP can be applied to non-numerical inputs like strings, dropdown selections, or file uploads. For example, if a dropdown menu has three options, each option represents a separate equivalence class.
By testing one representative value from each equivalence class, ECP eliminates the need to test every possible input, reducing redundancy. For instance, instead of testing all integers from 1-100, you can test just one value from the valid range and a few from invalid ranges.
ECP is typically used during the test design phase, especially for functional and system testing. It is most effective when the application has clearly defined input domains or ranges.
Yes, ECP is often combined with other techniques like Boundary Value Analysis (BVA) or Decision Table Testing to ensure comprehensive coverage of input domains and edge cases. For instance, you can use ECP for general partitioning and BVA to test the boundaries of those partitions.