AutoFraming: Synthesizing Dynamic Frames of C Code with LLMs

Han Zhou, Yu Luo, Dianxiang Xu

Large language models (LLMs) have shown considerable promise in synthesizing formal specifications from source code. However, existing approaches primarily focus on functional contracts and loop invariants, while largely neglecting frame conditions, which specify the memory locations that may or may not be modified during execution and constitute an essential part of formal specifications. To address this limitation, we propose an LLM-based approach for synthesizing ACSL frame specifications alongside functional contracts from C code. Our approach analyzes code property graphs (CPGs) to extract frame-relevant information from the input code and leverages this information to guide the LLM in generating accurate frame conditions. The resulting specifications capture both region-separation constraints and data dependencies that govern variable modifications. Experimental results demonstrate the effectiveness of our approach. On a benchmark of 84 ACSL-compliant functions from non-trivial real-world systems, our method successfully synthesizes error-free frame specifications for 92.9% of the functions, representing a 179% relative improvement over state-of-the-art techniques. On a…