Bayesian Optimisation of Solver Parameters in CBMC

Chaitanya Mangla, S. Holden, Lawrence Charles Paulson
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Abstract

Satisfiability solvers can be embedded in applications to perform specific formal reasoning tasks. CBMC, for example, is a bounded model checker for C and C++ that embeds SMT and SAT solvers to check internally generated formulae. Such solvers will be solely used to evaluate the class of formulae generated by the embedding application and therefore may benefit from domain-specific parameter tuning. We propose the use of Bayesian optimisation for this purpose, which offers a principled approach to black-box optimisation within limited resources. We demonstrate its use for optimisation of the solver embedded in CBMC specifically for a collection of test harnesses in active industrial use, for which we have achieved a significant improvement over the default parameters.
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CBMC中求解器参数的贝叶斯优化
可满足性求解器可以嵌入到应用程序中,以执行特定的形式推理任务。例如,CBMC是C和c++的有界模型检查器,它嵌入SMT和SAT求解器来检查内部生成的公式。这样的求解器将仅用于评估由嵌入应用程序生成的一类公式,因此可能受益于特定领域的参数调优。我们建议为此目的使用贝叶斯优化,它提供了在有限资源内进行黑盒优化的原则方法。我们演示了它用于优化嵌入在CBMC中的求解器,特别是用于活跃工业使用的一系列测试线束,我们已经实现了对默认参数的显着改进。
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