A dataflow analysis to improve SAT-based bounded program verification

SAT-based bounded verification of programs consists of the translation of the code and its annotations into a propositional formula. The formula is then analyzed for specification violations using a SAT-solver. This technique is capable of proving the absence of errors up to a given scope. SAT is a...

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Autores principales: Cuervo Parrino, B., Galeotti, J.P., Garbervetsky, D., Frias, M.F.
Formato: SER
Materias:
Bounded program verifications
Empirical evaluations
Logical representations
NP complete problems
Propositional formulas
Propositional variables
SAT solvers
SAT-based bounded verification
Verification tools
Computational complexity
Data flow analysis
Formal logic
Program translators
Verification
Formal methods
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_03029743_v7041LNCS_n_p138_CuervoParrino
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_03029743_v7041LNCS_n_p138_CuervoParrino
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spelling todo:paper_03029743_v7041LNCS_n_p138_CuervoParrino2023-10-03T15:19:22Z A dataflow analysis to improve SAT-based bounded program verification Cuervo Parrino, B. Galeotti, J.P. Garbervetsky, D. Frias, M.F. Bounded program verifications Empirical evaluations Logical representations NP complete problems Propositional formulas Propositional variables SAT solvers SAT-based bounded verification Verification tools Computational complexity Data flow analysis Formal logic Program translators Verification Formal methods SAT-based bounded verification of programs consists of the translation of the code and its annotations into a propositional formula. The formula is then analyzed for specification violations using a SAT-solver. This technique is capable of proving the absence of errors up to a given scope. SAT is a well-known NP-complete problem, whose complexity depends on the number of propositional variables occurring in the formula. Thus, reducing the number of variables in the logical representation may have a great impact on the overall analysis. We propose a dataflow analysis which infers the set of possible values that can be assigned to each local and instance variable. Unnecessary variables at the SAT level can then be safely removed by relying on the inferred values. We implemented this approach in TACO, a SAT-based verification tool. We present an extensive empirical evaluation and discuss the benefits of the proposed approach. © 2011 Springer-Verlag. Fil:Galeotti, J.P. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Garbervetsky, D. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Frias, M.F. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. SER info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_03029743_v7041LNCS_n_p138_CuervoParrino
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Bounded program verifications
Empirical evaluations
Logical representations
NP complete problems
Propositional formulas
Propositional variables
SAT solvers
SAT-based bounded verification
Verification tools
Computational complexity
Data flow analysis
Formal logic
Program translators
Verification
Formal methods
spellingShingle Bounded program verifications
Empirical evaluations
Logical representations
NP complete problems
Propositional formulas
Propositional variables
SAT solvers
SAT-based bounded verification
Verification tools
Computational complexity
Data flow analysis
Formal logic
Program translators
Verification
Formal methods
Cuervo Parrino, B.
Galeotti, J.P.
Garbervetsky, D.
Frias, M.F.
A dataflow analysis to improve SAT-based bounded program verification
topic_facet Bounded program verifications
Empirical evaluations
Logical representations
NP complete problems
Propositional formulas
Propositional variables
SAT solvers
SAT-based bounded verification
Verification tools
Computational complexity
Data flow analysis
Formal logic
Program translators
Verification
Formal methods
description SAT-based bounded verification of programs consists of the translation of the code and its annotations into a propositional formula. The formula is then analyzed for specification violations using a SAT-solver. This technique is capable of proving the absence of errors up to a given scope. SAT is a well-known NP-complete problem, whose complexity depends on the number of propositional variables occurring in the formula. Thus, reducing the number of variables in the logical representation may have a great impact on the overall analysis. We propose a dataflow analysis which infers the set of possible values that can be assigned to each local and instance variable. Unnecessary variables at the SAT level can then be safely removed by relying on the inferred values. We implemented this approach in TACO, a SAT-based verification tool. We present an extensive empirical evaluation and discuss the benefits of the proposed approach. © 2011 Springer-Verlag.
format SER
author Cuervo Parrino, B.
Galeotti, J.P.
Garbervetsky, D.
Frias, M.F.
author_facet Cuervo Parrino, B.
Galeotti, J.P.
Garbervetsky, D.
Frias, M.F.
author_sort Cuervo Parrino, B.
title A dataflow analysis to improve SAT-based bounded program verification
title_short A dataflow analysis to improve SAT-based bounded program verification
title_full A dataflow analysis to improve SAT-based bounded program verification
title_fullStr A dataflow analysis to improve SAT-based bounded program verification
title_full_unstemmed A dataflow analysis to improve SAT-based bounded program verification
title_sort dataflow analysis to improve sat-based bounded program verification
url http://hdl.handle.net/20.500.12110/paper_03029743_v7041LNCS_n_p138_CuervoParrino
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