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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)...
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| Publicat a: | Tools and Algorithms for the Construction and Analysis of Systems |
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| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2021
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| Matèries: | |
| Accés en línia: | 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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