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MachSMT: Machine Learning Driven Algorithm Selection for SMT Solvers

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 30 Nov 2022Publisher:Zenodo
Authors: Scott, Joseph; Niemetz, Aina; Preiner, Mathias; Nejati, Saeed; Ganesh, Vijay;

doi: 10.5281/zenodo.7383299 , 10.5281/zenodo.7383298

MachSMT: Machine Learning Driven Algorithm Selection for SMT Solvers

Abstract

This artifact contains the scripts, tools and data to replicate the experiments in the journal paper "MachSMT: Machine Learning Driven Algorithm Selection for SMT Solvers" accepted for publication in the STTT special issue dedicated to TACAS2021. Please refer to the README.md for further instructions.

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Keywords

Machine Learning, SMT Solvers, Algorithm Selection

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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