Verify the correctness of an addition function.

Express a test assertion for addition in unit testing.

When writing unit tests for a sum function or practicing test-driven development.

Python unit testing, educational exercises on functions and testing.

def test_sum(<arg1>, <arg2>, <expected>): assert <arg1> + <arg2> == <expected>

def test_sum(..., ..., ...): assert ... + ... == ...

a: first addend (int or float), b: second addend (int or float), expected: anticipated sum (int or float)

• test assert unit test addition function

• x: alternative name for first addend
• y: alternative name for second addend
• result: alternative name for expected sum

Incorrect argument order – cause: misunderstanding parameter positions; consequence: test fails despite correct function; Using wrong operator (e.g., -) – cause: confusing addition with subtraction; consequence: false test failures; Missing assert – cause: forgetting to assert equality; consequence: test passes regardless of function output; Failing to call the function under test – cause: asserting on raw parameters instead of function call; consequence: test does not exercise the target code

def test_sub(a,b,expected): assert a-b==expected – tests subtraction instead of addition; def test_mul(a,b,expected): assert a*b==expected – tests multiplication instead of addition

Coming from imperative languages: may assume parameter order matches function definition without checking – leads to incorrect assertions; Coming from math background: may confuse addition with subtraction – results in false test failures

• unit test patterns

Do not use this test when the function under test has side effects that affect the sum; Performance impact is negligible as the test is O(1); Boundary condition: floating‑point sums may require tolerance checks (e.g., using pytest.approx) rather than exact equality

Signals to readers that the code is a verification step, reinforcing test-driven development mindset.

Think of a simple addition test when learning to write unit tests.

Commonly used in introductory programming courses to teach both functions and unit testing.

Transition to using pytest's approx for floating-point numbers or parameterized tests.