@proffesor-for-testing/context-driven-testing
Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support testing activities for a product at any stage of the SDLC. Free to use, fork, build, and contribute. Based on the Agentic QE Framework created by Dragan Spiridonov.
| name | context-driven-testing |
| description | Apply context-driven testing principles where practices are chosen based on project context, not universal 'best practices'. Use when making testing decisions, questioning dogma, or adapting approaches to specific project needs. |
| category | testing-methodologies |
| priority | high |
| tokenEstimate | 1100 |
| agents | [qe-fleet-commander, qe-regression-risk-analyzer, qe-requirements-validator, qe-quality-analyzer] |
| implementation_status | optimized |
| optimization_version | 1.0 |
| last_optimized | 2025-12-02 |
| dependencies | [] |
| quick_reference_card | true |
| tags | [context-driven, rst, exploratory, heuristics, oracles, skilled-testing] |
| trust_tier | 0 |
Context-Driven Testing
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When making testing decisions or adapting approaches:
1. ANALYZE context: project goals, constraints, risks, team skills
2. QUESTION practices: "Why this? What risk does it address? What's the cost?"
3. INVESTIGATE not just check: Does software solve the problem, or create new ones?
4. ADAPT approach based on context, not "best practices"
5. DOCUMENT discoveries, not pre-written plans
Quick Context Analysis:
- Mission: "Find important problems fast enough to matter" (not "execute test cases")
- Risk: Safety-critical = high rigor; internal tool = lighter touch
- Constraints: Startup with tight timeline ≠ enterprise with compliance
- Skills: Novice needs structure; expert adapts intuitively
Critical Success Factors:
- No "best practices" work everywhere - only good practices in context
- Testing is investigation, not script execution
- Context changes; your approach should too
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Quick Reference Card
When to Use
- Making testing decisions for new project
- Questioning "that's how it's done" dogma
- Adapting approach to specific constraints
- Exploratory testing sessions
RST Heuristics
| Heuristic | Application |
|---|---|
| SFDIPOT | Structure, Function, Data, Interfaces, Platform, Operations, Time |
| Oracles | Consistency with history, similar products, expectations, docs |
| Tours | Business District, Historical, Bad Neighborhood, Tourist, Museum |
Context-Driven Decisions
Example: Test Automation Level
Startup Context:
- Small team, rapid changes, unclear product-market fit
- Decision: Light automation on critical paths, heavy exploratory
- Rationale: Requirements change too fast for extensive automation
Enterprise Context:
- Stable features, regulatory requirements, large team
- Decision: Comprehensive automated regression suite
- Rationale: Stability allows automation investment to pay off
Example: Documentation
Regulated (FDA/medical):
- Decision: Detailed test protocols, traceability matrices
- Rationale: Regulatory compliance isn't optional
Fast-paced startup:
- Decision: Lightweight session notes, risk logs
- Rationale: Bureaucracy slows more than it helps
Agent-Assisted Context-Driven Testing
// Agent analyzes context and recommends approach
const context = await Task("Analyze Context", {
project: 'e-commerce-platform',
stage: 'startup',
constraints: ['timeline: tight', 'budget: limited'],
risks: ['payment-security', 'high-volume']
}, "qe-fleet-commander");
// Context-aware agent selection
// - qe-security-scanner (critical risk)
// - qe-performance-tester (high volume)
// - Skip: qe-visual-tester (low priority in startup context)
// Adaptive testing strategy
await Task("Generate Tests", {
context: 'startup',
focus: 'critical-paths-only',
depth: 'smoke-tests',
automation: 'minimal'
}, "qe-test-generator");
Agent Coordination Hints
Memory Namespace
aqe/context-driven/
├── context-analysis/* - Project context snapshots
├── decisions/* - Testing decisions with rationale
├── discoveries/* - What was learned during testing
└── adaptations/* - How approach changed over time
Fleet Coordination
const contextFleet = await FleetManager.coordinate({
strategy: 'context-driven',
context: {
type: 'greenfield-saas',
stage: 'growth',
compliance: 'gdpr-only'
},
agents: ['qe-test-generator', 'qe-security-scanner', 'qe-performance-tester'],
exclude: ['qe-visual-tester', 'qe-requirements-validator'] // Not priority
});
Practical Tips
- Start with risk assessment - List features, ask: How likely to fail? How bad? How hard to test?
- Time-box exploration - 2 hours checkout, 30 min error handling, 15 min per browser
- Document discoveries - Not "Enter invalid email, verify error" but "Payment API returns 500 instead of 400, no user-visible error. Bug filed."
- Talk to humans - Developers, users, support, product
- Pair with others - Different perspectives = different bugs
Related Skills
- agentic-quality-engineering - Context-aware agent selection
- holistic-testing-pact - Adapt holistic model to context
- risk-based-testing - Context affects risk assessment
- exploratory-testing-advanced - RST techniques
Remember
With Agents: Agents analyze context, adapt strategies, and learn what works in your situation. Use agents to scale context-driven thinking while maintaining human judgment for critical decisions.
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