Method and system for generating test scenarios using artificial intelligence models

A system for generating test scenarios, the system comprising:

• a memory storing one or more instructions;
• at least one processor , in communication with the one or more instructions stored in the memory , configured to:
• extract configurable parameters and operable constraints from system information of a system-on-chip;
• aggregate use case information from a dataflow, the configurable parameters, and the operable constraints;
• identify, based on one or more artificial intelligence (AI) models , a hardware-software coordination mechanism based on the aggregated use case information;
• generate, based on the one or more AI models, a knowledge graph, wherein generating the knowledge graph further comprises creating a use case profile based on the aggregated use case information and the hardware-software coordination mechanism;
• instantiate at least a retrieval augmented generation agent configured to retrieve domain-specific information from the knowledge graph and a path optimization agent configured to determine traversal paths through the knowledge graph;
• generate, based on the one or more AI models, a test plan based on the use case profile, the domain-specific information, and the traversal paths associated with the knowledge graph;
• validate, based on the one or more AI models, the test plan by a human-in-the-loop verification agent;
• iteratively refine the test plan based on validation feedback from the human-in-the-loop verification agent;
• and
• generate, based on the one or more AI models, a plurality of test scenarios based on the validated and refined test plan.

A method for generating test scenarios, the method comprising:

• generating a knowledge graph, wherein generating the knowledge graph comprises creating a use case profile based on use case information and a hardware-software coordination mechanism;
• generating a test plan based on the use case profile, domain-specific information, and traversal paths associated with the knowledge graph;
• validating the test plan by a human-in-the-loop verification agent;
• iteratively refining the test plan based on validation feedback from the human-in-the-loop verification agent;
• and
• generating a plurality of test scenarios based on the validated and refined test plan