AI Testing

AI test generation analyzes your source code to understand what each function does, what inputs it accepts, what outputs it produces, and what edge cases exist. The AI then writes test cases that verify correct behavior, boundary conditions, error handling, and integration points. Unlike template-based test generators, AI-powered tools write tests that read like a human wrote them—with descriptive names, realistic test data, and logical groupings.

# Generate tests with Claude Code
$ claude
> "Write comprehensive tests for src/services/payment.ts.
   Cover: successful payment, insufficient funds, 
   network timeout, invalid card, duplicate charge 
   prevention, and currency conversion edge cases.
   Use the existing test patterns in __tests__/"

# The agent reads the source, understands the payment flow,
# and generates tests like:

describe("PaymentService", () => {
  it("should reject payment when card has insufficient funds", async () => {
    const card = createTestCard({ balance: 50 });
    const result = await paymentService.charge(card, 100);
    expect(result.status).toBe("declined");
    expect(result.reason).toBe("insufficient_funds");
  });

  it("should prevent duplicate charges within 60s window", async () => {
    const card = createTestCard({ balance: 1000 });
    await paymentService.charge(card, 100, { idempotencyKey: "abc" });
    const duplicate = await paymentService.charge(card, 100, { idempotencyKey: "abc" });
    expect(duplicate.status).toBe("duplicate");
  });
});

AI-generated tests are a starting point, not the finish line. Review them for correctness, ensure they test behavior (not implementation details), and verify they actually catch bugs. A test that always passes is worse than no test.