This research introduces an innovative approach that treats bug detection and bug-free coding as interconnected problems, using context-based Retrieval-Augmented Generation (RAG) to enhance AI-assisted software testing.

• Integrates code auto-completion and chatbot capabilities within a unified testing framework
• Leverages RAG to provide relevant context for more accurate bug detection
• Addresses efficiency bottlenecks in traditional testing methodologies
• Creates a symbiotic relationship between coding assistance and testing processes

For engineering teams, this approach offers a significant advantage by reducing development bottlenecks and improving code quality throughout the development lifecycle, not just at the testing phase.

From Code Generation to Software Testing: AI Copilot with Context-Based RAG