Towards SMT Solver Stability via Input Normalization

Fuente: arXiv
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Bibliographic Details
Main Authors: Amrollahi, Daneshvar, Preiner, Mathias, Niemetz, Aina, Reynolds, Andrew, Charikar, Moses, Tinelli, Cesare, Barrett, Clark
Format: Preprint
Published: 2024
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author Amrollahi, Daneshvar
Preiner, Mathias
Niemetz, Aina
Reynolds, Andrew
Charikar, Moses
Tinelli, Cesare
Barrett, Clark
author_facet Amrollahi, Daneshvar
Preiner, Mathias
Niemetz, Aina
Reynolds, Andrew
Charikar, Moses
Tinelli, Cesare
Barrett, Clark
contents In many applications, SMT solvers are utilized to solve similar or identical tasks over time. Significant variations in performance due to small changes in the input are not uncommon and lead to frustration for users. This sort of stability problem represents an important usability challenge for SMT solvers. We introduce an approach for mitigating the stability problem based on normalizing solver inputs. We show that a perfect normalizing algorithm exists but is computationally expensive. We then describe an approximate algorithm and evaluate it on a set of benchmarks from related work, as well as a large set of benchmarks sampled from SMT-LIB. Our evaluation shows that our approximate normalizer reduces runtime variability with minimal overhead and is able to normalize a large class of mutated benchmarks to a unique normal form.
format Preprint
id arxiv_https___arxiv_org_abs_2410_22419
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Towards SMT Solver Stability via Input Normalization
Amrollahi, Daneshvar
Preiner, Mathias
Niemetz, Aina
Reynolds, Andrew
Charikar, Moses
Tinelli, Cesare
Barrett, Clark
Logic in Computer Science
In many applications, SMT solvers are utilized to solve similar or identical tasks over time. Significant variations in performance due to small changes in the input are not uncommon and lead to frustration for users. This sort of stability problem represents an important usability challenge for SMT solvers. We introduce an approach for mitigating the stability problem based on normalizing solver inputs. We show that a perfect normalizing algorithm exists but is computationally expensive. We then describe an approximate algorithm and evaluate it on a set of benchmarks from related work, as well as a large set of benchmarks sampled from SMT-LIB. Our evaluation shows that our approximate normalizer reduces runtime variability with minimal overhead and is able to normalize a large class of mutated benchmarks to a unique normal form.
title Towards SMT Solver Stability via Input Normalization
topic Logic in Computer Science
url https://arxiv.org/abs/2410.22419