vibe-adversarial-test-generation

Generates edge case, failure mode, and spec-driven test cases. Covers boundary values, nil inputs, concurrency, resource exhaustion, malformed data, and requirement-linked traceability tests.

vibe-adversarial-test-generation

Happy-path tests prove your code works. Adversarial tests prove it doesn't break. Spec-linked tests prove it does what it's supposed to.

When to Use This Skill

  • After writing happy-path tests for a feature
  • Before claiming test coverage is complete
  • When spec requirements lack corresponding tests
  • When preparing for a security review
  • When vibe-spec-sync or vibe-coverage-enforcer reports uncovered requirements

When NOT to Use This Skill

  • Before happy-path tests exist (write those first)
  • For throwaway/prototype code
  • When the function is trivially simple (e.g., getters/setters)

Modes

Mode 1: Adversarial (Edge Cases)

Generate tests that break assumptions across 6 categories.

1. Boundary Values

  • Zero, one, max, max+1 for all numeric inputs
  • Empty string, single char, max-length string
  • Empty array, single element, very large array
  • Exactly at threshold values

2. Nil/Null/Undefined

  • nil pointer as receiver
  • nil arguments to every parameter
  • nil nested fields in structs
  • Returning nil where non-nil expected

3. Type Edge Cases

  • Unicode: emoji, RTL text, zero-width chars, combining chars
  • Strings: newlines, tabs, null bytes, control characters
  • Numbers: NaN, Infinity, -0, very large, very small
  • Dates: leap year, DST transitions, timezone boundaries, epoch

4. Concurrency

  • Two goroutines/threads calling the same function
  • Read during write
  • Close during use
  • Cancel during operation

5. Resource Exhaustion

  • Very large inputs (10MB string, 1M element slice)
  • Disk full simulation
  • Network timeout simulation
  • Memory pressure

6. Malformed Input

  • Invalid JSON/YAML/XML
  • Truncated input (cut off mid-field)
  • Wrong types (string where int expected)
  • Extra fields, missing required fields
  • SQL injection patterns, XSS payloads (for external inputs)

Mode 2: Spec-Driven (Requirement Coverage)

Generate tests that trace back to specific spec requirements.

  1. Read the spec — Find the specification document for the feature under test

  2. Extract requirements — Parse each requirement into an atomic, testable statement:

    • "Users can reset passwords via email" → testable
    • "The system should be fast" → not testable (flag it)
  3. Map existing tests to requirements — Scan test files for:

    • Comment markers: # req:[REQ-ID] or // req:[REQ-ID]
    • Function name patterns: test_req_[REQ-ID]_*
    • If no markers exist, use semantic matching (test name/body vs requirement text)
  4. Identify uncovered requirements — Requirements with no mapped tests

  5. Generate tests for uncovered requirements:

    • One test function per requirement minimum
    • Name format: test_req_[REQ-ID]_[description] (e.g., test_req_AUTH003_password_reset_sends_email)
    • First line of test body MUST include traceability marker:
      # req:AUTH-003
      
      // req:AUTH-003
      
      // req:AUTH-003
      
    • Test must assert actual behavior against the requirement, not just call the function
    • No skip(), no TODO, no empty bodies
  6. Report coverage delta:

    • Requirements covered before: X/N
    • Requirements covered after: Y/N
    • Remaining uncovered (with reasons — e.g., "requires external service mock")

Steps (Adversarial Mode)

  1. Read the function under test — understand inputs, outputs, side effects
  2. For each input parameter, generate adversarial values from each category
  3. For each adversarial input, determine expected behavior:
    • Should it return an error? (most common)
    • Should it handle gracefully? (fallback behavior)
    • Should it panic? (almost never the right answer)
  4. Write the tests as table-driven test cases
  5. Run them and fix any unexpected panics or wrong error handling

Steps (Spec-Driven Mode)

  1. Read the spec and extract atomic requirements with IDs
  2. Scan existing tests for requirement markers and semantic matches
  3. Generate a coverage map: requirement → test(s) or UNCOVERED
  4. Write tests for uncovered requirements with traceability markers
  5. Run tests and verify they pass against current implementation
  6. Report the before/after coverage delta

Output Format

Adversarial Tests: [Function Name]

Tests Generated: X Categories Covered: Y/6

#CategoryInputExpectedActual
1Nil inputnilErrNilInputPASS
2Empty string""ErrEmptyPANIC!

Issues Found

  1. [Function] panics on nil input (should return error)

Spec-Driven Tests: [Feature/Spec Name]

Spec: [path/to/spec.md] Requirements Found: N Previously Covered: X/N (Y%) Now Covered: Z/N (W%)

REQ IDRequirementTest StatusTest Function
AUTH-001Login requires email + passwordCoveredtest_req_AUTH001_login_requires_credentials
AUTH-002Failed login locks after 5 attemptsNEWtest_req_AUTH002_lockout_after_five_failures
AUTH-003Password reset sends emailUNCOVERED(requires email service mock)

Remaining Gaps

  1. AUTH-003: Requires email service mock — suggest adding mock in conftest.py