PeSCo: Predicting Sequential Combinations of Verifiers
Cedric Richter, Heike Wehrheim · Lecture notes in computer science · 2019
PeSCo is a tool for predicting a (likely best) sequential combination of verifiers on a given verification task and then running it. The approach is based on machine learning, more precisely on learning rankings of verifiers on verification tasks (where the ordering of verifiers is based on the SV-COMP scoring schema). The learning part employs Support Vector Machines; as base verifiers we use CPAchecker in 6 different configurations.