AI Application Testing Strategy: How to Test AI-Generated Code

Simi included in AI

2025-12-26 109 words One minute

Contents

AI Code Testing Specifics

AI code problems:
- edge cases easily missed
- possible hidden business logic errors
- need broader test coverage

Testing Strategy

        
        
        
    
# 1. prioritize edge cases
def test_calculate_discount_edge_cases():
    assert calculate_discount(0, 10) == 0  # amount is 0
    assert calculate_discount(100, 0) == 100  # discount is 0
    assert calculate_discount(100, 150) == 0  # discount over 100%
    assert calculate_discount(-10, 10) == 0  # negative amount

# 2. property-based testing
from hypothesis import given, strategies as st

@given(st.lists(st.floats(min_value=0, max_value=1000)))
def test_discount_properties(amounts):
    for amount in amounts:
        result = calculate_discount(amount, 10)
        assert 0 <= result <= amount

Conclusion

AI code testing: edge case priority + property testing + human review.