PURSE: Property Ordering Using Runtime Statistics for Efficient Multi - Property Verification

Multi-property verification has emerged as a con-temporary challenge in the chip design industry. With designs now encompassing hundreds of properties, conventional sequential verification without information sharing is no longer preferred. Past attempts towards grouping or ordering properties based on cone-of-influence (COI) are typically ineffective for complex designs. This paper introduces PURSE, a novel approach that addresses this challenge by dynamically reordering properties for sequential and incremental solving. By identifying and prioritizing simpler properties, the process accelerates convergence. This article presents two dynamic reordering techniques guided by statistical data gathered from the IC3/Property Directed Reachability (PDR) proof engine. The study compares dynamic ordering strategies against static ordering and a default ordering based on design structure. Empirical results from various industrial designs demonstrate that our proposed methodology performs better in most cases, with up to 25% improvements in convergence.