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MachSMT: A Machine Learning-based Algorithm Selector for SMT Solvers

In this paper, we present MachSMT, an algorithm selection tool for Satisfiability Modulo Theories (SMT) solvers. MachSMT supports the entirety of the SMT-LIB language. It employs machine learning (ML) methods to construct both empirical hardness models (EHMs) and pairwise ranking comparators (PWCs)...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:Tools and Algorithms for the Construction and Analysis of Systems
Egile Nagusiak: Scott, Joseph, Niemetz, Aina, Preiner, Mathias, Nejati, Saeed, Ganesh, Vijay
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: 2021
Gaiak:
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC7984560/
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-72013-1_16
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