Parallel Program Analysis via Range Splitting.

Ranged symbolic execution has been proposed as a way of scaling symbolic execution by splitting the task of path exploration onto several workers running in parallel. The split is conducted along path ranges which – simply speaking – describe sets of paths. Workers can then explore path ranges in parallel. In this paper, we propose ranged analysis as the generalization of ranged symbolic execution to arbitrary program analyses. This allows us to not only parallelize a single analysis, but also run different analyses on different ranges of a program in parallel. Besides this generalization, we also provide a novel range splitting strategy operating along loop bounds, complementing the existing random strategy of the original proposal. We implemented ranged analysis within the tool CPAchecker and evaluated it on programs from the SV-COMP benchmark. The evaluation in particular shows the superiority of loop bounds splitting over random splitting. We furthermore find that compositions of ranged analyses can solve analysis tasks that none of the constituent analysis alone can solve.