Testing Methodologies
Effective testing of AI systems requires a comprehensive approach that combines multiple methodologies to ensure safety, security, and reliability. Giskard provides tools and frameworks for implementing robust testing strategies.
Key testing approaches
Section titled “Key testing approaches” Business Failures AI system failures that affect the business logic of the model.
Security Vulnerabilities AI system failures that affect the security of the model.
LLM Scan Giskard's automated vulnerability detection system that identifies security issues and business logic failures.
RAG Evaluation A comprehensive testing framework for Retrieval-Augmented Generation systems.
Adversarial Testing Testing methodology that intentionally tries to break or exploit models using carefully crafted inputs.
Human-in-the-Loop Combining automated testing with human expertise and judgment.
Regression Testing Ensuring that new changes don't break existing functionality.
Continuous Red Teaming Automated, ongoing security testing that continuously monitors for new threats and vulnerabilities.
Testing lifecycle
Section titled “Testing lifecycle”1. Planning phase
Section titled “1. Planning phase”- Define testing objectives and scope
- Identify critical vulnerabilities and risks
- Design test strategies and methodologies
- Establish success criteria and metrics
2. Execution phase
Section titled “2. Execution phase”- Implement automated testing frameworks
- Conduct manual testing and validation
- Perform adversarial and red team testing
- Monitor and record results
3. Analysis phase
Section titled “3. Analysis phase”- Evaluate test results and findings
- Prioritize vulnerabilities and issues
- Generate comprehensive reports
- Plan remediation strategies
4. Remediation phase
Section titled “4. Remediation phase”- Address identified vulnerabilities
- Implement fixes and improvements
- Re-test to verify resolution
- Update testing procedures
Best practices
Section titled “Best practices”- Comprehensive Coverage: Test all critical functionality and edge cases
- Regular Updates: Keep testing frameworks and methodologies current
- Documentation: Maintain detailed testing procedures and results
- Automation: Automate repetitive testing tasks for efficiency
- Human Oversight: Combine automated testing with human expertise