AI Research

Exploring applications of Retrieval Augmented Generation in software testing, including test case generation, coverage analysis, and testing strategy recommendations.

Exploring Model Context Protocol applications in software testing, examining how standardized AI-tool communication can revolutionize test automation and create context-aware testing frameworks.

Investigating autonomous AI agents for software testing, from existing platform integration to specialized testing agent development and multi-agent orchestration systems.

Comprehensive analysis of testing approaches for Large Language Models, including hallucination detection, bias measurement, and safety validation frameworks.

Research into quantifiable metrics for AI safety, including prompt injection detection, output toxicity measurement, and model reliability scoring.

Analysis of emerging patterns in AI-augmented test automation, including test generation, maintenance, and execution optimization strategies.