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10-test-suites

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Test Suites

Validation Layer — Verifying implementations against specification requirements

Definition

Test suites are collections of automated tests that verify system behavior. In a specification-grounded ecosystem, tests serve as executable verification that an implementation fulfills its specification requirements.

Relationship to the Specification

The specification defines what must be true. Tests verify that it is true. Every testable requirement in the specification should have corresponding tests.

Specification RequirementTest Verifies
”Messages must not exceed 64KB”Sending 65KB message returns error
”Authentication required before data exchange”Unauthenticated requests are rejected
”Responses within 500ms”Latency measurements under load
”At-least-once delivery”Messages eventually arrive despite failures

Test Categories

Unit Tests

Verify individual components implement specification behaviors:

def test_message_size_limit():
    """SPEC-3.4.1: Messages must not exceed 64KB"""
    large_message = b"x" * 65537  # 64KB + 1
    with pytest.raises(MessageTooLargeError):
        validate_message(large_message)

Integration Tests

Verify components interact per specification:

def test_handshake_sequence():
    """SPEC-2.1: Connection requires completed handshake"""
    client = Client()
    # Attempting to send before handshake should fail
    with pytest.raises(NotConnectedError):
        client.send(message)
    # After handshake, should succeed
    client.connect()
    assert client.send(message).success

Conformance Tests

Verify protocol-level specification compliance:

def test_message_format_conformance():
    """SPEC-3.2.1: Message wire format"""
    message = encode_message(content="hello")
    # Verify byte-level format matches specification
    assert message[0:4] == expected_header
    assert message[-64:] == expected_signature_length

Dependency Chain

Specification
    ↓
Test Suites ← executable verification of requirements
    ↓
Compliance Checks ← formal conformance validation
    ↓
Audit Trails ← evidence of verification
    ↓
Code & Comments ← tested implementation

Why Spec-Grounding Matters

Tests without specification grounding verify what code does, not what code should do:

  • Testing implementation bugs: Tests pass but behavior violates specification
  • Missing coverage: Untested specification requirements remain unverified
  • Regression blindness: Changes that break spec compliance go undetected
  • False confidence: High test coverage with low specification coverage

Specification Traceability

Every test should trace to specification requirements:

class TestMessageDelivery:
    """Tests for SPEC-4.2 (Message Delivery)"""
    
    @spec_requirement("SPEC-4.2.1")
    def test_message_acceptance(self):
        """Verify messages are accepted for delivery"""
        pass
    
    @spec_requirement("SPEC-4.2.3")
    def test_delivery_timeout(self):
        """Verify 500ms delivery SLA"""
        pass
    
    @spec_requirement("SPEC-4.2.5")
    def test_at_least_once_delivery(self):
        """Verify messages are not silently dropped"""
        pass

This enables:

  • Coverage reports showing which spec requirements have tests
  • Impact analysis when specifications change
  • Gap identification for untested requirements

Test Vector Suites

For protocols and data formats, specifications should include test vectors—canonical input/output pairs that any compliant implementation must handle correctly:

## Test Vectors for SPEC-3.2.1 (Message Encoding)
 
### Vector 1: Minimal Message
Input:
    content: ""
    sender: 0x00...00 (32 zero bytes)
    
Expected Output (hex):
    00000000 00000000 00000000 00000000
    00000000 00000000 00000000 00000000
    ... (signature bytes)
 
### Vector 2: Maximum Size Message
Input:
    content: (64KB of 0x41 bytes)
    ...

Best Practices

  • Require specification references for all tests
  • Generate coverage reports showing spec requirements vs. test coverage
  • Include specification test vectors in conformance test suites
  • Run tests against multiple implementations to verify spec clarity
  • Update tests when specifications change—tests are documentation too
  • Treat failing tests as either implementation bugs OR specification ambiguity
  • Use property-based testing for specification invariants

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