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/test-design-techniques

Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.

From plugin
agentic-qe
436200 skills169 agents149 commands
Install
$ npx -y skills add proffesor-for-testing/agentic-qe --skill test-design-techniques --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/test-design-techniques

Context preview

The summary Claude sees to decide when to auto-load this skill.

Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.

SKILL.md

test-design-techniques.SKILL.md
name: test-design-techniques
description: "Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage."
category: specialized-testing
priority: high
tokenEstimate: 900
agents: [qe-test-generator, qe-coverage-analyzer, qe-quality-analyzer]
implementation_status: optimized
optimization_version: 1.0
last_optimized: 2025-12-02
dependencies: []
quick_reference_card: true
tags: [test-design, bva, equivalence-partitioning, decision-tables, pairwise, state-transition]
trust_tier: 3
validation:
  schema_path: schemas/output.json
  validator_path: scripts/validate-config.json
  eval_path: evals/test-design-techniques.yaml

Test Design Techniques

<default_to_action> When designing test cases, select technique by input type:

  • Numeric ranges → BVA + EP
  • Multiple conditions → Decision Tables
  • Workflows → State Transition
  • Many parameter combinations → Pairwise Testing

</default_to_action>

Quick Reference Card

When to Use

  • Designing new test suites
  • Optimizing existing tests
  • Complex business rules
  • Reducing test redundancy

---

Agent-Driven Test Design

// Auto-generate BVA tests
await Task("Generate BVA Tests", {
  field: 'age',
  dataType: 'integer',
  constraints: { min: 18, max: 120 }
}, "qe-test-generator");
// Returns: 6 boundary test cases

// Auto-generate pairwise tests
await Task("Generate Pairwise Tests", {
  parameters: {
    browser: ['Chrome', 'Firefox', 'Safari'],
    os: ['Windows', 'Mac', 'Linux'],
    screen: ['Desktop', 'Tablet', 'Mobile']
  }
}, "qe-test-generator");
// Returns: 9-12 tests (vs 27 full combination)

---

Agent Coordination Hints

Memory Namespace

aqe/test-design/
├── bva-analysis/*       - Boundary value tests
├── partitions/*         - Equivalence partitions
├── decision-tables/*    - Decision table tests
└── pairwise/*           - Combinatorial reduction

Fleet Coordination

const designFleet = await FleetManager.coordinate({
  strategy: 'systematic-test-design',
  agents: [
    'qe-test-generator',    // Apply design techniques
    'qe-coverage-analyzer', // Analyze coverage
    'qe-quality-analyzer'   // Assess test quality
  ],
  topology: 'sequential'
});

---

Related Skills

  • [agentic-quality-engineering](../agentic-quality-engineering/) - Agent-driven testing
  • [risk-based-testing](../risk-based-testing/) - Prioritize by risk
  • [mutation-testing](../mutation-testing/) - Validate test effectiveness

---

Remember

**With Agents:** `qe-test-generator` applies these techniques automatically, generating optimal test suites with maximum coverage and minimum redundancy. Agents identify boundaries, partitions, and combinations from code analysis.

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