Cauliflower, a Solver Generator for Context-Free Language Reachability

Abstract

Context-free language reachability (CFL-R) is a fundamental solving vehicle for computing essential compiler optimisations and static program analyses. Unfortunately, solvers for CFL- R encounter both inherently expensive problem formulations and frequent alterations to the underlying formalism. As such, tool designers are forced to create custom-tailored implementations with long development times and limited reusability. A better framework is crucial to facilitate research and development in CFL-R.

In this work we present Cauliflower, a CFL-R solver generator, that creates parallel executable C++ code from an input CFL-R rule-based specification. With Cauliflower, developers create working tools rapidly, avoiding lengthy and error-prone manual implementations. Cauliflower’s domain-specific language provides semantic extension including reversal, branch- ing, disconnection and templating. In practical experiments, Cauliflower achieves an average speedup of 1.8x compared with the best general purpose tools, and matches the performance of application-specific tools on many benchmarks.

Collaborators

• Nicholas Hollingum
• Bernhard Scholz

Links

• 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning