Assertion Generation

Assertion generation focuses on automatically creating formal statements that describe program or system behavior, primarily to aid in verification and validation. Current research heavily utilizes large language models (LLMs), often enhanced with techniques like prompt engineering and in-context learning, to generate assertions from various sources, including natural language specifications, code, and execution traces. This automated approach aims to improve efficiency and accuracy in tasks ranging from hardware verification and software testing to clinical natural language processing, ultimately leading to more robust and reliable systems.