What is pairwise testing and what is its essence?

Pairwise testing is a test design technique based on a combinatorial approach.

The essence of pairwise testing is that most defects are detected through the interaction of two system parameters out of all possible. Therefore, to minimize test cases while achieving a high level of coverage, all possible pairs of different input parameter values can be tested instead of testing all possible combinations.

Advantages:

• Reduction in the number of test cases compared to full combinatorial testing.
• Increased testing efficiency, as most defects are related to the simultaneous influence of two parameters.
• A systematic approach to covering parameter combinations.

Disadvantages:

• It does not guarantee the detection of defects that occur with interactions of more than two parameters.
• It requires the use of special tools or algorithms to generate test sets.

Example: Testing a registration form with fields "User Type" (Administrator, User), "Role" (Choice 1, Choice 2, Choice 3), and "Status" (Active, Inactive).

Full combinatorial testing: 2 * 3 * 2 = 12 test cases.

Pairwise testing using a tool:

User Type	Role	Status
Administrator	Choice 1	Active
User	Choice 2	Inactive
Administrator	Choice 3	Active
User	Choice 1	Inactive
Administrator	Choice 2	Active
User	Choice 3	Inactive

In this example, pairwise testing can generate 6 test cases, covering all possible pairs of values.

Algorithms such as IPO (In Parameter Order) or CA (Covering Arrays) are used, which are implemented in specialized tools (e.g., PICT from Microsoft, Allpairs, TestCovering).

# Example of using the pairwise library (may require installation: pip install pairwise)
from pairwise import pairwise

parameters = {
    'user_type': ['Admin', 'User'],
    'role': ['Role1', 'Role2', 'Role3'],
    'status': ['Active', 'Inactive']
}

# Generate pairwise combinations
test_cases = pairwise(parameters)

# Output the generated test cases
for case in test_cases:
    print(case)