Please tell me about the test design techniques you have worked with and know.

Test design techniques help systematize the process of creating test cases to cover functionality and reduce the number of missed errors. Here are the main techniques I have worked with:

• Equivalence Partitioning — dividing input data into equivalence classes, assuming that the system's behavior is the same for all values within a class. For example, for the "age" field, classes can be: negative values, 0-18, 19-65, >65.

• Boundary Value Analysis — testing values at the edges of equivalence classes, as errors often occur there. For example, if age should be from 18 to 65, test 17, 18, 19, 64, 65, 66.

• Pairwise Testing — for systems with multiple parameters, it covers all pairs of parameter values, significantly reducing the number of tests while maintaining good coverage.

• Cause-Effect Graphing — building a graph of dependencies between conditions and outcomes, which helps identify complex logical scenarios.

• State Transition Testing — useful for systems with finite automata, where transitions between states are important.

• Use Case Testing — testing the system through real user scenarios.

Example of using equivalence partitioning and boundary value analysis:

# Checking a function that accepts the user's age
def is_adult(age):
    return age >= 18

# Tests
assert not is_adult(17)  # below the boundary
assert is_adult(18)      # at the boundary
assert is_adult(30)      # within the class