Fast Client-Driven CFL-Reachability via Regularization-Based Graph Simplification

Abstract

Context-free language (CFL) reachability is a critical framework for various program analyses, widely adopted despite its computational challenges due to cubic or near-cubic time complexity. This often leads to significant performance degradation in client applications. Notably, in real-world scenarios, clients typically require reachability information only for specific source-to-sink pairs, offering opportunities for targeted optimization.

We introduce MoYe, an effective regularization-based graph simplification technique designed to enhance the performance of client-driven CFL-reachability analyses by pruning non-contributing edges—those that do not participate in any specified CFL-reachable paths. MoYe employs a regular approximation to ensure exact reachability results for all designated node pairs and operates linearly with respect to the number of edges in the graph. This lightweight efficiency makes MoYe a valuable pre-processing step that substantially reduces both computational time and memory requirements for CFL-reachability analysis, outperforming a recent leading graph simplification approach. Our evaluations with two prominent CFL-reachability client applications demonstrate that MoYe can substantially improve performance and reduce resource consumption.