  Various static analysis problems are reformulated as instances of the
Context-Free Language Reachability (CFL-r) problem. One promising way to make
solving CFL-r more practical for large-scale interprocedural graphs is to
reduce CFL-r to linear algebra operations on sparse matrices, as they are
efficiently executed on modern hardware. In this work, we present five
optimizations for a matrix-based CFL-r algorithm that utilize the specific
properties of both the underlying semiring and the widely-used linear algebra
library SuiteSparse:GraphBlas. Our experimental results show that these
optimizations result in orders of magnitude speedup, with the optimized
matrix-based CFL-r algorithm consistently outperforming state-of-the-art CFL-r
solvers across four considered static analyses.
