# Satisfiability modulo theories

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Logical problem studied in computer science

In [computer science](/source/Computer_science) and [mathematical logic](/source/Mathematical_logic), **satisfiability modulo theories** (**SMT**) is the [problem](/source/Decision_problem) of determining whether a [mathematical formula](/source/Well-formed_formula) is [satisfiable](/source/Satisfiability). It generalizes the [Boolean satisfiability problem](/source/Boolean_satisfiability_problem) (SAT) to more complex formulas involving [real numbers](/source/Real_numbers), [integers](/source/Integers), and/or various [data structures](/source/Data_structure) such as [lists](/source/List_(computing)), [arrays](/source/Array_data_structure), [bit vectors](/source/Bit_vector), and [strings](/source/String_(computer_science)). The name is derived from the fact that these expressions are interpreted within ("modulo") a certain [formal theory](/source/Theory_(mathematical_logic)) in [first-order logic with equality](/source/First-order_logic) (often disallowing [quantifiers](/source/Quantifier_(logic))). **SMT solvers** are tools that aim to solve the SMT problem for a practical subset of inputs. SMT solvers such as [Z3](/source/Z3_Theorem_Prover) and [cvc5](/source/Cvc5) have been used as a building block for a wide range of applications across computer science, including in [automated theorem proving](/source/Automated_theorem_proving), [program analysis](/source/Program_analysis), [program verification](/source/Formal_verification), and [software testing](/source/White-box_testing).

Since Boolean satisfiability is already [NP-complete](/source/NP-complete), the SMT problem is typically [NP-hard](/source/NP-hardness), and for many theories it is [undecidable](/source/Undecidable_problem). Researchers study which theories or subsets of theories lead to a decidable SMT problem and the [computational complexity](/source/Computational_complexity) of decidable cases. The resulting decision procedures are often implemented directly in SMT solvers; see, for instance, the decidability of [Presburger arithmetic](/source/Presburger_arithmetic). SMT can be thought of as a [constraint satisfaction problem](/source/Constraint_satisfaction_problem) and thus a certain formalized approach to [constraint programming](/source/Constraint_programming).

## Terminology and examples

Formally speaking, an SMT instance is a [formula](/source/Well-formed_formula) in [first-order logic](/source/First-order_logic), where some function and predicate symbols have additional interpretations, and SMT is the problem of determining whether such a formula is satisfiable. In other words, imagine an instance of the [Boolean satisfiability problem](/source/Boolean_satisfiability_problem) (SAT) in which some of the [binary variables](/source/Binary_data) are replaced by [predicates](/source/Predicate_(mathematical_logic)) over a suitable set of non-binary variables. A predicate is a binary-valued function of non-binary variables. Example predicates include linear [inequalities](/source/Inequality_(mathematics)) (e.g., 3 x + 2 y − z ≥ 4 {\displaystyle 3x+2y-z\geq 4} ) or equalities involving [uninterpreted terms](/source/Uninterpreted_term) and function symbols (e.g., f ( f ( u , v ) , v ) = f ( u , v ) {\displaystyle f(f(u,v),v)=f(u,v)} where f {\displaystyle f} is some unspecified function of two arguments). These predicates are classified according to each respective theory assigned. For instance, linear inequalities over [real](/source/Real_number) variables are evaluated using the rules of the theory of linear real [arithmetic](/source/Arithmetic), whereas predicates involving uninterpreted terms and function symbols are evaluated using the rules of the theory of [uninterpreted functions](/source/Uninterpreted_function) with equality (sometimes referred to as the [empty theory](/source/Empty_theory)). Other theories include the theories of [arrays](/source/Array_data_structure) and [list](/source/List_(computing)) structures (useful for modeling and verifying [computer programs](/source/Computer_program)), and the theory of [bit vectors](/source/Bit_vectors) (useful in modeling and verifying [hardware designs](/source/Hardware_design)). Subtheories are also possible: for example, difference logic is a sub-theory of linear arithmetic in which each inequality is restricted to have the form x − y > c {\displaystyle x-y>c} for variables x {\displaystyle x} and y {\displaystyle y} and constant c {\displaystyle c} .

The examples above show the use of linear integer arithmetic over inequalities. Other examples include:

- Satisfiability: Determine if x ∨ ( y ∧ ¬ z ) {\displaystyle x\vee (y\wedge \neg z)} is satisfiable.

- Array access: Find a value for array *A* such that *A*[0] = 5.

- Bit vector arithmetic: Determine if *x* and *y* are distinct 3-bit numbers.

- Uninterpreted functions: Find values for *x* and *y* such that f ( x ) = 2 {\displaystyle f(x)=2} and g ( x ) = 3 {\displaystyle g(x)=3} .

Most SMT solvers support only [quantifier](/source/Quantifier_(logic))-free fragments of their logics.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

## Relationship to automated theorem proving

There is substantial overlap between SMT solving and [automated theorem proving](/source/Automated_theorem_proving) (ATP). Generally, automated theorem provers focus on supporting full first-order logic with quantifiers, whereas SMT solvers focus more on supporting various theories (interpreted predicate symbols). ATPs excel at problems with lots of quantifiers, whereas SMT solvers do well on large problems without quantifiers.[1] The line is blurry enough that some ATPs participate in SMT-COMP, while some SMT solvers participate in [CASC](/source/CADE_ATP_System_Competition).[2]

## Expressive power

An SMT instance is a generalization of a [Boolean SAT](/source/Boolean_satisfiability_problem) instance in which various sets of variables are replaced by [predicates](/source/Predicate_(mathematical_logic)) from a variety of underlying theories. SMT formulas provide a much richer [modeling language](/source/Modeling_language) than is possible with Boolean SAT formulas. For example, an SMT formula allows one to model the [datapath](/source/Datapath) operations of a [microprocessor](/source/Microprocessor) at the word rather than the bit level.

By comparison, [answer set programming](/source/Answer_set_programming) is also based on predicates (more precisely, on [atomic sentences](/source/Atomic_sentence) created from [atomic formulas](/source/Atomic_formula)). Unlike SMT, answer-set programs do not have quantifiers, and cannot easily express constraints such as linear arithmetic or [difference logic](https://en.wikipedia.org/w/index.php?title=Difference_logic&action=edit&redlink=1)—answer set programming is best suited to Boolean problems that reduce to the [free theory](/source/Free_theory) of uninterpreted functions. Implementing 32-bit integers as bitvectors in answer set programming suffers from most of the same problems that early SMT solvers faced: "obvious" identities such as *x* + *y* = *y* + *x* are difficult to deduce.

[Constraint logic programming](/source/Constraint_logic_programming) does provide support for linear arithmetic constraints, but within a completely different theoretical framework.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] SMT solvers have also been extended to solve formulas in [higher-order logic](/source/Higher-order_logic).[3]

## Solver approaches

Early attempts for solving SMT instances involved translating them to Boolean SAT instances (e.g., a 32-bit integer variable would be encoded by 32 single-bit variables with appropriate weights and word-level operations such as 'plus' would be replaced by lower-level logic operations on the bits) and passing this formula to a Boolean SAT solver. This approach, which is referred to as *the [eager](/source/Eager_evaluation) approach* (or *bitblasting*), has its merits: by pre-processing the SMT formula into an equivalent Boolean SAT formula existing Boolean SAT solvers can be used "as-is" and their performance and capacity improvements leveraged over time. On the other hand, the loss of the high-level semantics of the underlying theories means that the Boolean SAT solver has to work a lot harder than necessary to discover "obvious" facts (such as x + y = y + x {\displaystyle x+y=y+x} for integer addition.) This observation led to the development of a number of SMT solvers that tightly integrate the Boolean reasoning of a [DPLL](/source/DPLL_algorithm)-style search with theory-specific solvers (*T-solvers*) that handle [conjunctions](/source/Logical_conjunction) (ANDs) of predicates from a given theory. This approach is referred to as *the [lazy](/source/Lazy_evaluation) approach*.[4]

Dubbed [DPLL(T)](/source/DPLL(T)),[5] this architecture gives the responsibility of Boolean reasoning to the DPLL-based SAT solver which, in turn, interacts with a solver for theory T through a well-defined interface. The theory solver only needs to worry about checking the feasibility of conjunctions of theory predicates passed on to it from the SAT solver as it explores the Boolean search space of the formula. For this integration to work well, however, the theory solver must be able to participate in propagation and conflict analysis, i.e., it must be able to infer new facts from already established facts, as well as to supply succinct explanations of infeasibility when theory conflicts arise. In other words, the theory solver must be incremental and [backtrackable](/source/Backtracking).

## Decidable theories

Researchers study which theories or subsets of theories lead to a decidable SMT problem and the [computational complexity](/source/Computational_complexity) of decidable cases. Since full [first-order logic](/source/First-order_logic) is only [semidecidable](/source/Semidecidable), one line of research attempts to find efficient decision procedures for fragments of first-order logic such as [effectively propositional logic](/source/Effectively_propositional_logic).[6]

Another line of research involves the development of specialized [decidable theories](/source/Decidability_(logic)), including linear arithmetic over [rationals](/source/Rational_number) and [integers](/source/Integer), fixed-width bitvectors,[7] [floating-point arithmetic](/source/Floating-point_arithmetic) (often implemented in SMT solvers via *bit-blasting*, i.e., reduction to bitvectors),[8][9] [strings](/source/String_(computer_science)),[10] [(co)-datatypes](/source/Data_type),[11] [sequences](/source/Sequence) (used to model [dynamic arrays](/source/Dynamic_array)),[12] finite [sets](/source/Set_(mathematics)) and [relations](/source/Relation_(mathematics)),[13][14] [separation logic](/source/Separation_logic),[15] [finite fields](/source/Finite_field),[16] and [uninterpreted functions](/source/Uninterpreted_function) among others.

*Boolean monotonic theories* are a class of theory that support efficient theory propagation and conflict analysis, enabling practical use within DPLL(T) solvers.[17] Monotonic theories support only Boolean variables (Boolean is the only *sort*), and all their functions and predicates p obey the axiom

- p ( … , b i − 1 , 0 , b i + 1 , … ) ⟹ p ( … , b i − 1 , 1 , b i + 1 , … ) {\displaystyle p(\ldots ,b_{i-1},0,b_{i+1},\ldots )\implies p(\ldots ,b_{i-1},1,b_{i+1},\ldots )}

Examples of monotonic theories include [graph reachability](/source/Reachability), collision detection for [convex hulls](/source/Convex_hull), [minimum cuts](/source/Minimum_cut), and [computation tree logic](/source/Computation_tree_logic).[18] Every [Datalog](/source/Datalog) program can be interpreted as a monotonic theory.[19]

## SMT for undecidable theories

Most of the common SMT approaches support [decidable](/source/Decidability_(logic)) theories. However, many real-world systems, such as an aircraft and its behavior, can only be modelled by means of non-linear arithmetic over the real numbers involving [transcendental functions](/source/Transcendental_function). This fact motivates an extension of the SMT problem to non-linear theories, such as determining whether the following equation is satisfiable:

- ( sin ⁡ ( x ) 3 = cos ⁡ ( log ⁡ ( y ) ⋅ x ) ∨ b ∨ − x 2 ≥ 2.3 y ) ∧ ( ¬ b ∨ y < − 34.4 ∨ exp ⁡ ( x ) > y x ) {\displaystyle {\begin{array}{lr}&(\sin(x)^{3}=\cos(\log(y)\cdot x)\vee b\vee -x^{2}\geq 2.3y)\wedge \left(\neg b\vee y<-34.4\vee \exp(x)>{y \over x}\right)\end{array}}}

where

- b ∈ B , x , y ∈ R . {\displaystyle b\in {\mathbb {B} },x,y\in {\mathbb {R} }.}

Such problems are, however, [undecidable](/source/Undecidable_problem) in general. (On the other hand, the theory of [real closed fields](/source/Real_closed_field), and thus the full first order theory of the [real numbers](/source/Real_number), are [decidable](/source/Decidability_(logic)) using [quantifier elimination](/source/Quantifier_elimination). This is due to [Alfred Tarski](/source/Alfred_Tarski).) The first order theory of the [natural numbers](/source/Natural_numbers) with addition (but not multiplication), called [Presburger arithmetic](/source/Presburger_arithmetic), is also decidable. Since multiplication by constants can be implemented as nested additions, the arithmetic in many computer programs can be expressed using Presburger arithmetic, resulting in decidable formulas.

Examples of SMT solvers addressing Boolean combinations of theory atoms from undecidable arithmetic theories over the reals are ABsolver,[20] which employs a classical DPLL(T) architecture with a non-linear optimization packet as (necessarily incomplete) subordinate theory solver, [iSAT](http://isat.gforge.avacs.org/), building on a unification of DPLL SAT-solving and [interval constraint propagation](/source/Interval_arithmetic#Interval_arithmetic) called the iSAT algorithm,[21] and [cvc5](/source/Cvc5).[22]

## Solvers

The table below summarizes some of the features of the many available SMT solvers. The column "SMT-LIB" indicates compatibility with the SMT-LIB language; many systems marked 'yes' may support only older versions of SMT-LIB, or offer only partial support for the language. The column "CVC" indicates support for the CVC language. The column "DIMACS" indicates support for the [DIMACS](/source/DIMACS) [format](http://www.satcompetition.org/2009/format-benchmarks2009.html).

Projects differ not only in features and performance, but also in the viability of the surrounding community, its ongoing interest in a project, and its ability to contribute documentation, fixes, tests and enhancements.

Platform Features Notes Name OS License SMT-LIB CVC DIMACS Built-in theories API SMT-COMP [1] ABsolver Linux CPL v1.2 No Yes linear arithmetic, non-linear arithmetic C++ no DPLL-based Alt-Ergo Linux, Mac OS, Windows CeCILL-C (roughly equivalent to LGPL) partial v1.2 and v2.0 No No empty theory, linear integer and rational arithmetic, non-linear arithmetic, polymorphic arrays, enumerated datatypes, AC symbols, bitvectors, record datatypes, quantifiers OCaml 2008 Polymorphic first-order input language à la ML, SAT-solver based, combines Shostak-like and Nelson-Oppen like approaches for reasoning modulo theories Barcelogic Linux Proprietary v1.2 empty theory, difference logic C++ 2009 DPLL-based, congruence closure Beaver Linux, Windows BSD v1.2 No No bitvectors OCaml 2009 SAT-solver based Boolector Linux MIT v1.2 No No bitvectors, arrays C 2009 SAT-solver based CVC3 Linux BSD v1.2 Yes empty theory, linear arithmetic, arrays, tuples, types, records, bitvectors, quantifiers C/C++ 2010 proof output to HOL CVC4 Linux, Mac OS, Windows, FreeBSD BSD Yes Yes rational and integer linear arithmetic, arrays, tuples, records, inductive data types, bitvectors, strings, and equality over uninterpreted function symbols C++ 2021 version 1.8 released May 2021 cvc5 Linux, Mac OS, Windows BSD Yes Yes rational and integer linear arithmetic, arrays, tuples, records, inductive data types, bitvectors, finite fields, strings, sequences, bags, and equality over uninterpreted function symbols C++, Python, Java 2021 version 1.0 released April 2022 Decision Procedure Toolkit (DPT) Linux Apache No OCaml no DPLL-based iSAT Linux Proprietary No non-linear arithmetic no DPLL-based MathSAT Linux, Mac OS, Windows Proprietary Yes Yes empty theory, linear arithmetic, nonlinear arithmetic, bitvectors, arrays C/C++, Python, Java 2010 DPLL-based MiniSmt Linux LGPL partial v2.0 non-linear arithmetic OCaml 2010 SAT-solver based, Yices-based Norn SMT solver for string constraints OpenCog Linux AGPL No No No probabilistic logic, arithmetic. relational models C++, Scheme, Python no subgraph isomorphism OpenSMT Linux, Mac OS, Windows GPLv3 partial v2.0 Yes empty theory, differences, linear arithmetic, bitvectors C++ 2011 lazy SMT Solver raSAT Linux GPLv3 v2.0 real and integer nonlinear arithmetic 2014, 2015 extension of the Interval Constraint Propagation with Testing and the Intermediate Value Theorem SatEEn ? Proprietary v1.2 linear arithmetic, difference logic none 2009 SMTInterpol Linux, Mac OS, Windows LGPLv3 v2.5 uninterpreted functions, linear real arithmetic, and linear integer arithmetic Java 2012 Focuses on generating high quality, compact interpolants. SMCHR Linux, Mac OS, Windows GPLv3 No No No linear arithmetic, nonlinear arithmetic, heaps C no Can implement new theories using Constraint Handling Rules. SMT-RAT Linux, Mac OS MIT v2.0 No No linear arithmetic, nonlinear arithmetic C++ 2015 Toolbox for strategic and parallel SMT solving consisting of a collection of SMT compliant implementations. SONOLAR Linux, Windows Proprietary partial v2.0 bitvectors C 2010 SAT-solver based Spear Linux, Mac OS, Windows Proprietary v1.2 bitvectors 2008 STP Linux, OpenBSD, Windows, Mac OS MIT partial v2.0 Yes No bitvectors, arrays C, C++, Python, OCaml, Java 2011 SAT-solver based SWORD Linux Proprietary v1.2 bitvectors 2009 UCLID Linux BSD No No No empty theory, linear arithmetic, bitvectors, and constrained lambda (arrays, memories, cache, etc.) no SAT-solver based, written in Moscow ML. Input language is SMV model checker. Well-documented! veriT Linux, OS X BSD partial v2.0 empty theory, rational and integer linear arithmetics, quantifiers, and equality over uninterpreted function symbols C/C++ 2010 SAT-solver based, can produce proofs Yices Linux, Mac OS, Windows, FreeBSD GPLv3 v2.0 No Yes rational and integer linear arithmetic, bitvectors, arrays, and equality over uninterpreted function symbols C 2014 Source code is available online Z3 Theorem Prover Linux, Mac OS, Windows, FreeBSD MIT v2.0 Yes empty theory, linear arithmetic, nonlinear arithmetic, bitvectors, arrays, datatypes, quantifiers, strings C/C++, .NET, OCaml, Python, Java, Haskell 2011 Source code is available online

### Standardization and the SMT-COMP solver competition

There are multiple attempts to describe a standardized interface to SMT solvers (and [automated theorem provers](/source/Automated_theorem_proving), a term often used synonymously). The most prominent is the SMT-LIB standard,[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] which provides a language based on [S-expressions](/source/S-expression). Other standardized formats commonly supported are the DIMACS format[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] supported by many Boolean SAT solvers, and the CVC format[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] used by the CVC automated theorem prover.

The SMT-LIB format also comes with a number of standardized benchmarks and has enabled a yearly competition between SMT solvers called SMT-COMP. Initially, the competition took place during the [Computer Aided Verification](/source/Computer_Aided_Verification) conference (CAV),[23][24] but as of 2020 the competition is hosted as part of the SMT Workshop, which is affiliated with the [International Joint Conference on Automated Reasoning](/source/International_Joint_Conference_on_Automated_Reasoning) (IJCAR).[25]

## Applications

SMT solvers are useful both for verification, proving the [correctness](/source/Correctness_(computer_science)) of programs, software testing based on [symbolic execution](/source/Symbolic_execution), and for [synthesis](/source/Program_synthesis), generating program fragments by searching over the space of possible programs. Outside of software verification, SMT solvers have also been used for [type inference](/source/Type_inference)[26][27] and for modelling theoretic scenarios, including modelling actor beliefs in nuclear [arms control](/source/Arms_control).[28]

### Verification

Computer-aided [verification of computer programs](/source/Formal_verification) often uses SMT solvers. A common technique is to translate preconditions, postconditions, loop conditions, and assertions into SMT formulas in order to determine if all properties can hold.

There are many verifiers built on top of the [Z3 SMT solver](/source/Z3_Theorem_Prover). [Boogie](http://research.microsoft.com/en-us/projects/boogie/) is an intermediate verification language that uses Z3 to automatically check simple imperative programs. The [VCC](https://www.microsoft.com/en-us/research/project/vcc-a-verifier-for-concurrent-c/) verifier for concurrent C uses Boogie, as well as [Dafny](http://research.microsoft.com/en-us/projects/dafny/) for imperative object-based programs, [Chalice](http://research.microsoft.com/en-us/projects/chalice/) for concurrent programs, and [Spec#](http://research.microsoft.com/en-us/projects/specsharp/) for C#. [F*](http://research.microsoft.com/en-us/projects/fstar/) is a dependently typed language that uses Z3 to find proofs; the compiler carries these proofs through to produce proof-carrying bytecode. The [Viper verification infrastructure](http://viper.ethz.ch) encodes verification conditions to Z3. The [sbv](https://hackage.haskell.org/package/sbv) library provides SMT-based verification of Haskell programs, and lets the user choose among a number of solvers such as Z3, ABC, Boolector, cvc5, MathSAT and Yices.

There are also many verifiers built on top of the [Alt-Ergo](http://alt-ergo.ocamlpro.com/) SMT solver. Here is a list of mature applications:

- [Why3](http://why3.lri.fr/), a platform for deductive program verification, uses Alt-Ergo as its main prover;

- CAVEAT, a C-verifier developed by CEA and used by Airbus; Alt-Ergo was included in the qualification DO-178C of one of its recent aircraft;

- [Frama-C](/source/Frama-C), a framework to analyse C-code, uses Alt-Ergo in the Jessie and WP plugins (dedicated to "deductive program verification");

- [SPARK](/source/SPARK_(programming_language)) uses CVC4 and Alt-Ergo (behind GNATprove) to automate the verification of some assertions in SPARK 2014;

- [Atelier-B](/source/B-Method) can use Alt-Ergo instead of its main prover (increasing success from 84% to 98% on the [ANR Bware project benchmarks](http://alt-ergo.lri.fr/documents/ABZ-2014.pdf) [Archived](https://web.archive.org/web/20141129015810/http://alt-ergo.lri.fr/documents/ABZ-2014.pdf) 2014-11-29 at the [Wayback Machine](/source/Wayback_Machine));

- [Rodin](/source/Rodin_tool), a B-method framework developed by Systerel, can use Alt-Ergo as a back-end;

- [Cubicle](http://cubicle.lri.fr/), an open source model checker for verifying safety properties of array-based transition systems.

- [EasyCrypt](https://www.easycrypt.info/), a toolset for reasoning about relational properties of probabilistic computations with adversarial code.

Many SMT solvers implement a common interface format called [SMTLIB2](http://smt-lib.org/) (such files usually have the extension ".smt2"). The [LiquidHaskell](https://ucsd-progsys.github.io/liquidhaskell-blog/) tool implements a refinement type based verifier for Haskell that can use any SMTLIB2 compliant solver, e.g. cvc5, MathSat, or Z3.

### Symbolic-execution based analysis and testing

An important application of SMT solvers is [symbolic execution](/source/Symbolic_execution) for analysis and testing of programs (e.g., [concolic testing](/source/Concolic_testing)), aimed particularly at finding security vulnerabilities.[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*] Example tools in this category include [SAGE](http://research.microsoft.com/en-us/um/people/pg/public_psfiles/ndss2008.pdf) from [Microsoft Research](/source/Microsoft_Research), [KLEE](https://klee.github.io/), [S2E](http://s2e.epfl.ch/), and [Triton](https://triton.quarkslab.com). SMT solvers that have been used for symbolic-execution applications include [Z3](https://github.com/Z3Prover/z3), [STP](https://sites.google.com/site/stpfastprover/) [Archived](https://web.archive.org/web/20150406115407/https://sites.google.com/site/stpfastprover/) 2015-04-06 at the [Wayback Machine](/source/Wayback_Machine), the [Z3str family of solvers](https://z3string.github.io/), and [Boolector](http://fmv.jku.at/boolector/).[*[citation needed](https://en.wikipedia.org/wiki/Wikipedia:Citation_needed)*]

### Interactive theorem proving

SMT solvers have been integrated with proof assistants, including [Rocq](/source/Rocq)[29] and [Isabelle/HOL](/source/Isabelle%2FHOL).[30]

### Synthesis

SMT solvers are a core building block in [program synthesis](/source/Program_synthesis), the automated generation of programs from specifications. A prominent approach is [counterexample-guided inductive synthesis](https://en.wikipedia.org/w/index.php?title=Counterexample-guided_inductive_synthesis&action=edit&redlink=1) (CEGIS), in which a synthesiser proposes a candidate program that is verified by an SMT solver; counterexamples from failed checks guide the synthesiser until a correct solution is found.[31]

A related application is [automatic program repair](/source/Automatic_bug_fixing): given a buggy program and a test suite, an SMT formula is constructed whose solution yields a patch. For example, Nopol encodes the problem of finding a repaired conditional expression as an SMT instance, translating the solution back into a source-code patch for Java programs.[32]

## See also

- [Answer set programming](/source/Answer_set_programming)

- [Automated theorem proving](/source/Automated_theorem_proving)

- [SAT solver](/source/Boolean_satisfiability_problem#Algorithms_for_solving_SAT)

- [First-order logic](/source/First-order_logic)

- [Theory of pure equality](/source/Theory_of_pure_equality)

## Notes

1. **[^](#cite_ref-1)** Blanchette, Jasmin Christian; Böhme, Sascha; Paulson, Lawrence C. (2013-06-01). ["Extending Sledgehammer with SMT Solvers"](https://doi.org/10.1007/s10817-013-9278-5). *Journal of Automated Reasoning*. **51** (1): 109–128. [doi](/source/Doi_(identifier)):[10.1007/s10817-013-9278-5](https://doi.org/10.1007%2Fs10817-013-9278-5). [ISSN](/source/ISSN_(identifier)) [1573-0670](https://search.worldcat.org/issn/1573-0670). ATPs and SMT solvers have complementary strengths. The former handle quantifiers more elegantly, whereas the latter excel on large, mostly ground problems.

1. **[^](#cite_ref-2)** Weber, Tjark; Conchon, Sylvain; Déharbe, David; Heizmann, Matthias; Niemetz, Aina; Reger, Giles (2019-01-01). ["The SMT Competition 2015–2018"](https://doi.org/10.3233%2FSAT190123). *Journal on Satisfiability, Boolean Modeling and Computation*. **11** (1): 221–259. [doi](/source/Doi_(identifier)):[10.3233/SAT190123](https://doi.org/10.3233%2FSAT190123). [S2CID](/source/S2CID_(identifier)) [210147712](https://api.semanticscholar.org/CorpusID:210147712). In recent years, we have seen a blurring of lines between SMT-COMP and CASC with SMT solvers competing in CASC and ATPs competing in SMT-COMP.

1. **[^](#cite_ref-3)** Barbosa, Haniel; Reynolds, Andrew; El Ouraoui, Daniel; Tinelli, Cesare; Barrett, Clark (2019). ["Extending SMT solvers to higher-order logic"](https://hal.archives-ouvertes.fr/hal-02300986/document). *Automated Deduction – CADE 27: 27th International Conference on Automated Deduction, Natal, Brazil, August 27–30, 2019, Proceedings*. Springer. pp. 35–54. [doi](/source/Doi_(identifier)):[10.1007/978-3-030-29436-6_3](https://doi.org/10.1007%2F978-3-030-29436-6_3). [ISBN](/source/ISBN_(identifier)) [978-3-030-29436-6](https://en.wikipedia.org/wiki/Special:BookSources/978-3-030-29436-6). [S2CID](/source/S2CID_(identifier)) [85443815](https://api.semanticscholar.org/CorpusID:85443815). hal-02300986.

1. **[^](#cite_ref-4)** Bruttomesso, Roberto; Cimatti, Alessandro; Franzén, Anders; Griggio, Alberto; Hanna, Ziyad; Nadel, Alexander; Palti, Amit; Sebastiani, Roberto (2007). ["A Lazy and Layered SMT( $\mathcal{BV}$ ) Solver for Hard Industrial Verification Problems"](https://link.springer.com/chapter/10.1007/978-3-540-73368-3_54). In Damm, Werner; Hermanns, Holger (eds.). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 4590. Berlin, Heidelberg: Springer. pp. 547–560. [doi](/source/Doi_(identifier)):[10.1007/978-3-540-73368-3_54](https://doi.org/10.1007%2F978-3-540-73368-3_54). [ISBN](/source/ISBN_(identifier)) [978-3-540-73368-3](https://en.wikipedia.org/wiki/Special:BookSources/978-3-540-73368-3).

1. **[^](#cite_ref-5)** Nieuwenhuis, R.; Oliveras, A.; Tinelli, C. (2006), ["Solving SAT and SAT Modulo Theories: From an Abstract Davis-Putnam-Logemann-Loveland Procedure to DPLL(T)"](http://homepage.cs.uiowa.edu/~tinelli/papers/NieOT-JACM-06.pdf) (PDF), *[Journal of the ACM](/source/Journal_of_the_ACM)*, vol. 53, pp. 937–977, [doi](/source/Doi_(identifier)):[10.1145/1217856.1217859](https://doi.org/10.1145%2F1217856.1217859), [S2CID](/source/S2CID_(identifier)) [14058631](https://api.semanticscholar.org/CorpusID:14058631)

1. **[^](#cite_ref-6)** de Moura, Leonardo; Bjørner, Nikolaj (August 12–15, 2008). ["Deciding Effectively Propositional Logic Using DPLL and Substitution Sets"](https://link.springer.com/chapter/10.1007/978-3-540-71070-7_35). In Armando, Alessandro; Baumgartner, Peter; Dowek, Gilles (eds.). *Automated Reasoning*. 4th International Joint Conference on Automated Reasoning, Sydney, NSW, Australia. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer. pp. 410–425. [doi](/source/Doi_(identifier)):[10.1007/978-3-540-71070-7_35](https://doi.org/10.1007%2F978-3-540-71070-7_35). [ISBN](/source/ISBN_(identifier)) [978-3-540-71070-7](https://en.wikipedia.org/wiki/Special:BookSources/978-3-540-71070-7).

1. **[^](#cite_ref-7)** Hadarean, Liana; Bansal, Kshitij; Jovanović, Dejan; Barrett, Clark; Tinelli, Cesare (2014). ["A Tale of Two Solvers: Eager and Lazy Approaches to Bit-Vectors"](https://link.springer.com/chapter/10.1007/978-3-319-08867-9_45). In Biere, Armin; Bloem, Roderick (eds.). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 8559. Cham: Springer International Publishing. pp. 680–695. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-08867-9_45](https://doi.org/10.1007%2F978-3-319-08867-9_45). [ISBN](/source/ISBN_(identifier)) [978-3-319-08867-9](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-08867-9).

1. **[^](#cite_ref-8)** Brain, Martin; Schanda, Florian; Sun, Youcheng (2019). "Building Better Bit-Blasting for Floating-Point Problems". In Vojnar, Tomáš; Zhang, Lijun (eds.). *Tools and Algorithms for the Construction and Analysis of Systems*. 25th International Conference, Tools and Algorithms for the Construction and Analysis of Systems 2019, Prague, Czech Republic, April 6–11, 2019, Proceedings, Part I. Lecture Notes in Computer Science. Cham: Springer International Publishing. pp. 79–98. [doi](/source/Doi_(identifier)):[10.1007/978-3-030-17462-0_5](https://doi.org/10.1007%2F978-3-030-17462-0_5). [ISBN](/source/ISBN_(identifier)) [978-3-030-17462-0](https://en.wikipedia.org/wiki/Special:BookSources/978-3-030-17462-0). [S2CID](/source/S2CID_(identifier)) [92999474](https://api.semanticscholar.org/CorpusID:92999474).

1. **[^](#cite_ref-9)** Brain, Martin; Niemetz, Aina; Preiner, Mathias; Reynolds, Andrew; Barrett, Clark; Tinelli, Cesare (2019). "Invertibility Conditions for Floating-Point Formulas". In Dillig, Isil; Tasiran, Serdar (eds.). *Computer Aided Verification*. 31st International Conference, Computer Aided Verification 2019, New York City, July 15–18, 2019. Lecture Notes in Computer Science. Cham: Springer International Publishing. pp. 116–136. [doi](/source/Doi_(identifier)):[10.1007/978-3-030-25543-5_8](https://doi.org/10.1007%2F978-3-030-25543-5_8). [ISBN](/source/ISBN_(identifier)) [978-3-030-25543-5](https://en.wikipedia.org/wiki/Special:BookSources/978-3-030-25543-5). [S2CID](/source/S2CID_(identifier)) [196613701](https://api.semanticscholar.org/CorpusID:196613701).

1. **[^](#cite_ref-10)** Liang, Tianyi; Tsiskaridze, Nestan; Reynolds, Andrew; Tinelli, Cesare; Barrett, Clark (2015). ["A Decision Procedure for Regular Membership and Length Constraints over Unbounded Strings"](https://link.springer.com/chapter/10.1007/978-3-319-24246-0_9). In Lutz, Carsten; Ranise, Silvio (eds.). *Frontiers of Combining Systems*. Lecture Notes in Computer Science. Vol. 9322. Cham: Springer International Publishing. pp. 135–150. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-24246-0_9](https://doi.org/10.1007%2F978-3-319-24246-0_9). [ISBN](/source/ISBN_(identifier)) [978-3-319-24246-0](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-24246-0).

1. **[^](#cite_ref-11)** Reynolds, Andrew; Blanchette, Jasmin Christian (2015). ["A Decision Procedure for (Co)datatypes in SMT Solvers"](https://link.springer.com/chapter/10.1007/978-3-319-21401-6_13). In Felty, Amy P.; Middeldorp, Aart (eds.). *Automated Deduction - CADE-25*. Lecture Notes in Computer Science. Vol. 9195. Cham: Springer International Publishing. pp. 197–213. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-21401-6_13](https://doi.org/10.1007%2F978-3-319-21401-6_13). [ISBN](/source/ISBN_(identifier)) [978-3-319-21401-6](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-21401-6).

1. **[^](#cite_ref-12)** Sheng, Ying; Nötzli, Andres; Reynolds, Andrew; Zohar, Yoni; Dill, David; Grieskamp, Wolfgang; Park, Junkil; Qadeer, Shaz; Barrett, Clark; Tinelli, Cesare (2023-09-15). ["Reasoning About Vectors: Satisfiability Modulo a Theory of Sequences"](https://doi.org/10.1007/s10817-023-09682-2). *Journal of Automated Reasoning*. **67** (3): 32. [doi](/source/Doi_(identifier)):[10.1007/s10817-023-09682-2](https://doi.org/10.1007%2Fs10817-023-09682-2). [ISSN](/source/ISSN_(identifier)) [1573-0670](https://search.worldcat.org/issn/1573-0670). [S2CID](/source/S2CID_(identifier)) [261829653](https://api.semanticscholar.org/CorpusID:261829653).

1. **[^](#cite_ref-13)** Bansal, Kshitij; Reynolds, Andrew; Barrett, Clark; Tinelli, Cesare (2016). ["A New Decision Procedure for Finite Sets and Cardinality Constraints in SMT"](https://link.springer.com/chapter/10.1007/978-3-319-40229-1_7). In Olivetti, Nicola; Tiwari, Ashish (eds.). *Automated Reasoning*. Lecture Notes in Computer Science. Vol. 9706. Cham: Springer International Publishing. pp. 82–98. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-40229-1_7](https://doi.org/10.1007%2F978-3-319-40229-1_7). [ISBN](/source/ISBN_(identifier)) [978-3-319-40229-1](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-40229-1).

1. **[^](#cite_ref-14)** Meng, Baoluo; Reynolds, Andrew; Tinelli, Cesare; Barrett, Clark (2017). ["Relational Constraint Solving in SMT"](https://link.springer.com/chapter/10.1007/978-3-319-63046-5_10). In de Moura, Leonardo (ed.). *Automated Deduction – CADE 26*. Lecture Notes in Computer Science. Vol. 10395. Cham: Springer International Publishing. pp. 148–165. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-63046-5_10](https://doi.org/10.1007%2F978-3-319-63046-5_10). [ISBN](/source/ISBN_(identifier)) [978-3-319-63046-5](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-63046-5).

1. **[^](#cite_ref-15)** Reynolds, Andrew; Iosif, Radu; Serban, Cristina; King, Tim (2016). ["A Decision Procedure for Separation Logic in SMT"](https://hal.science/hal-01418883). In Artho, Cyrille; Legay, Axel; Peled, Doron (eds.). *Automated Technology for Verification and Analysis*. Lecture Notes in Computer Science. Vol. 9938. Cham: Springer International Publishing. pp. 244–261. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-46520-3_16](https://doi.org/10.1007%2F978-3-319-46520-3_16). [ISBN](/source/ISBN_(identifier)) [978-3-319-46520-3](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-46520-3). [S2CID](/source/S2CID_(identifier)) [6753369](https://api.semanticscholar.org/CorpusID:6753369).

1. **[^](#cite_ref-16)** Ozdemir, Alex; Kremer, Gereon; Tinelli, Cesare; Barrett, Clark (2023). ["Satisfiability Modulo Finite Fields"](https://link.springer.com/chapter/10.1007/978-3-031-37703-7_8). In Enea, Constantin; Lal, Akash (eds.). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 13965. Cham: Springer Nature Switzerland. pp. 163–186. [doi](/source/Doi_(identifier)):[10.1007/978-3-031-37703-7_8](https://doi.org/10.1007%2F978-3-031-37703-7_8). [ISBN](/source/ISBN_(identifier)) [978-3-031-37703-7](https://en.wikipedia.org/wiki/Special:BookSources/978-3-031-37703-7). [S2CID](/source/S2CID_(identifier)) [257235627](https://api.semanticscholar.org/CorpusID:257235627).

1. **[^](#cite_ref-17)** Bayless, Sam; Bayless, Noah; Hoos, Holger; Hu, Alan (2015-03-04). ["SAT Modulo Monotonic Theories"](https://ojs.aaai.org/index.php/AAAI/article/view/9755). *Proceedings of the AAAI Conference on Artificial Intelligence*. **29** (1). [arXiv](/source/ArXiv_(identifier)):[1406.0043](https://arxiv.org/abs/1406.0043). [doi](/source/Doi_(identifier)):[10.1609/aaai.v29i1.9755](https://doi.org/10.1609%2Faaai.v29i1.9755). [ISSN](/source/ISSN_(identifier)) [2374-3468](https://search.worldcat.org/issn/2374-3468). [S2CID](/source/S2CID_(identifier)) [9567647](https://api.semanticscholar.org/CorpusID:9567647).

1. **[^](#cite_ref-18)** Klenze, Tobias; Bayless, Sam; Hu, Alan J. (2016). ["Fast, Flexible, and Minimal CTL Synthesis via SMT"](https://link.springer.com/chapter/10.1007/978-3-319-41528-4_8). In Chaudhuri, Swarat; Farzan, Azadeh (eds.). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 9779. Cham: Springer International Publishing. pp. 136–156. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-41528-4_8](https://doi.org/10.1007%2F978-3-319-41528-4_8). [ISBN](/source/ISBN_(identifier)) [978-3-319-41528-4](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-41528-4).

1. **[^](#cite_ref-19)** Bembenek, Aaron; Greenberg, Michael; Chong, Stephen (2023-01-11). ["From SMT to ASP: Solver-Based Approaches to Solving Datalog Synthesis-as-Rule-Selection Problems"](https://doi.org/10.1145%2F3571200). *Proceedings of the ACM on Programming Languages*. **7** (POPL): 7:185–7:217. [doi](/source/Doi_(identifier)):[10.1145/3571200](https://doi.org/10.1145%2F3571200). [S2CID](/source/S2CID_(identifier)) [253525805](https://api.semanticscholar.org/CorpusID:253525805).

1. **[^](#cite_ref-20)** Bauer, A.; Pister, M.; Tautschnig, M. (2007), "Tool-support for the analysis of hybrid systems and models", *Proceedings of the 2007 Conference on Design, Automation and Test in Europe (DATE'07)*, IEEE Computer Society, p. 1, [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.323.6807](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.323.6807), [doi](/source/Doi_(identifier)):[10.1109/DATE.2007.364411](https://doi.org/10.1109%2FDATE.2007.364411), [ISBN](/source/ISBN_(identifier)) [978-3-9810801-2-4](https://en.wikipedia.org/wiki/Special:BookSources/978-3-9810801-2-4), [S2CID](/source/S2CID_(identifier)) [9159847](https://api.semanticscholar.org/CorpusID:9159847)

1. **[^](#cite_ref-21)** Fränzle, M.; Herde, C.; Ratschan, S.; Schubert, T.; Teige, T. (2007), ["Efficient Solving of Large Non-linear Arithmetic Constraint Systems with Complex Boolean Structure"](http://jsat.ewi.tudelft.nl/content/volume1/JSAT1_11_Fraenzle.pdf) (PDF), *Journal on Satisfiability, Boolean Modeling and Computation*, **1** (3–4 JSAT Special Issue on SAT/CP Integration): 209–236, [doi](/source/Doi_(identifier)):[10.3233/SAT190012](https://doi.org/10.3233%2FSAT190012)

1. **[^](#cite_ref-22)** Barbosa, Haniel; Barrett, Clark; Brain, Martin; Kremer, Gereon; Lachnitt, Hanna; Mann, Makai; Mohamed, Abdalrhman; Mohamed, Mudathir; Niemetz, Aina; Nötzli, Andres; Ozdemir, Alex; Preiner, Mathias; Reynolds, Andrew; Sheng, Ying; Tinelli, Cesare (2022). ["cvc5: A Versatile and Industrial-Strength SMT Solver"](https://link.springer.com/chapter/10.1007/978-3-030-99524-9_24). In Fisman, Dana; Rosu, Grigore (eds.). *Tools and Algorithms for the Construction and Analysis of Systems, 28th International Conference*. Lecture Notes in Computer Science. Vol. 13243. Cham: Springer International Publishing. pp. 415–442. [doi](/source/Doi_(identifier)):[10.1007/978-3-030-99524-9_24](https://doi.org/10.1007%2F978-3-030-99524-9_24). [ISBN](/source/ISBN_(identifier)) [978-3-030-99524-9](https://en.wikipedia.org/wiki/Special:BookSources/978-3-030-99524-9). [S2CID](/source/S2CID_(identifier)) [247857361](https://api.semanticscholar.org/CorpusID:247857361).

1. **[^](#cite_ref-23)** Barrett, Clark; de Moura, Leonardo; Stump, Aaron (2005). ["SMT-COMP: Satisfiability Modulo Theories Competition"](https://link.springer.com/chapter/10.1007%2F11513988_4). In Etessami, Kousha; Rajamani, Sriram K. (eds.). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 3576. Springer. pp. 20–23. [doi](/source/Doi_(identifier)):[10.1007/11513988_4](https://doi.org/10.1007%2F11513988_4). [ISBN](/source/ISBN_(identifier)) [978-3-540-31686-2](https://en.wikipedia.org/wiki/Special:BookSources/978-3-540-31686-2).

1. **[^](#cite_ref-24)** Barrett, Clark; de Moura, Leonardo; Ranise, Silvio; Stump, Aaron; Tinelli, Cesare (2011). "The SMT-LIB Initiative and the Rise of SMT: (HVC 2010 Award Talk)". In Barner, Sharon; Harris, Ian; Kroening, Daniel; Raz, Orna (eds.). *Hardware and Software: Verification and Testing*. Lecture Notes in Computer Science. Vol. 6504. Springer. p. 3. [Bibcode](/source/Bibcode_(identifier)):[2011LNCS.6504....3B](https://ui.adsabs.harvard.edu/abs/2011LNCS.6504....3B). [doi](/source/Doi_(identifier)):[10.1007/978-3-642-19583-9_2](https://doi.org/10.1007%2F978-3-642-19583-9_2). [ISBN](/source/ISBN_(identifier)) [978-3-642-19583-9](https://en.wikipedia.org/wiki/Special:BookSources/978-3-642-19583-9).

1. **[^](#cite_ref-25)** ["SMT-COMP 2020"](https://smt-comp.github.io/2020/). *SMT-COMP*. Retrieved 2020-10-19.

1. **[^](#cite_ref-26)** Hassan, Mostafa; Urban, Caterina; Eilers, Marco; Müller, Peter (2018). ["MaxSMT-Based Type Inference for Python 3"](https://link.springer.com/chapter/10.1007/978-3-319-96142-2_2). *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 10982. pp. 12–19. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-96142-2_2](https://doi.org/10.1007%2F978-3-319-96142-2_2). [ISBN](/source/ISBN_(identifier)) [978-3-319-96141-5](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-96141-5).

1. **[^](#cite_ref-27)** Loncaric, Calvin, et al. ["A practical framework for type inference error explanation."](https://manu.sridharan.net/files/mycroft-preprint.pdf) ACM SIGPLAN Notices 51.10 (2016): 781-799.

1. **[^](#cite_ref-28)** Beaumont, Paul; Evans, Neil; Huth, Michael; Plant, Tom (2015). "Confidence Analysis for Nuclear Arms Control: SMT Abstractions of Bayesian Belief Networks". In Pernul, Günther; Y A Ryan, Peter; Weippl, Edgar (eds.). *Computer Security -- ESORICS 2015*. Lecture Notes in Computer Science. Vol. 9326. Springer. pp. 521–540. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-24174-6_27](https://doi.org/10.1007%2F978-3-319-24174-6_27). [ISBN](/source/ISBN_(identifier)) [978-3-319-24174-6](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-24174-6).

1. **[^](#cite_ref-29)** Ekici, Burak; Mebsout, Alain; Tinelli, Cesare; Keller, Chantal; Katz, Guy; Reynolds, Andrew; Barrett, Clark (2017). ["SMTCoq: A Plug-In for Integrating SMT Solvers into Coq"](https://hal.science/hal-01669345). In Majumdar, Rupak; Kunčak, Viktor (eds.). *Computer Aided Verification, 29th International Conference*. Lecture Notes in Computer Science. Vol. 10427. Cham: Springer International Publishing. pp. 126–133. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-63390-9_7](https://doi.org/10.1007%2F978-3-319-63390-9_7). [ISBN](/source/ISBN_(identifier)) [978-3-319-63390-9](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-63390-9). [S2CID](/source/S2CID_(identifier)) [206701576](https://api.semanticscholar.org/CorpusID:206701576).

1. **[^](#cite_ref-30)** Blanchette, Jasmin Christian; Böhme, Sascha; Paulson, Lawrence C. (2013-06-01). ["Extending Sledgehammer with SMT Solvers"](https://doi.org/10.1007/s10817-013-9278-5). *Journal of Automated Reasoning*. **51** (1): 109–128. [doi](/source/Doi_(identifier)):[10.1007/s10817-013-9278-5](https://doi.org/10.1007%2Fs10817-013-9278-5). [ISSN](/source/ISSN_(identifier)) [1573-0670](https://search.worldcat.org/issn/1573-0670).

1. **[^](#cite_ref-31)** Abate, Alessandro; David, Cristina; Kesseli, Pascal; Kroening, Daniel; Polgreen, Elizabeth (2018). "Counterexample Guided Inductive Synthesis Modulo Theories". *Computer Aided Verification*. Lecture Notes in Computer Science. Vol. 10981. pp. 270–288. [doi](/source/Doi_(identifier)):[10.1007/978-3-319-96145-3_15](https://doi.org/10.1007%2F978-3-319-96145-3_15). [ISBN](/source/ISBN_(identifier)) [978-3-319-96144-6](https://en.wikipedia.org/wiki/Special:BookSources/978-3-319-96144-6).

1. **[^](#cite_ref-32)** Xuan, Jifeng; Martinez, Matias; DeMarco, Favio; Clement, Maxime; Marcote, Sebastian Lamelas; Durieux, Thomas; Le Berre, Daniel; Monperrus, Martin (January 2017). "Nopol: Automatic Repair of Conditional Statement Bugs in Java Programs". *IEEE Transactions on Software Engineering*. **43** (1): 34–55. [arXiv](/source/ArXiv_(identifier)):[1811.04211](https://arxiv.org/abs/1811.04211). [Bibcode](/source/Bibcode_(identifier)):[2017ITSEn..43...34X](https://ui.adsabs.harvard.edu/abs/2017ITSEn..43...34X). [doi](/source/Doi_(identifier)):[10.1109/tse.2016.2560811](https://doi.org/10.1109%2Ftse.2016.2560811).

## References

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- Kroening, D.; Strichman, O. (2008). [*Decision Procedures — an algorithmic point of view*](https://books.google.com/books?id=anJsH3Dq5BIC&q=SMT). Theoretical Computer Science series. Springer. [ISBN](/source/ISBN_(identifier)) [978-3-540-74104-6](https://en.wikipedia.org/wiki/Special:BookSources/978-3-540-74104-6).

- Nam, G.-J.; Sakallah, K.A.; Rutenbar, R. (2002). "A New FPGA Detailed Routing Approach via Search-Based Boolean Satisfiability". *IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems*. **21** (6): 674–684. [Bibcode](/source/Bibcode_(identifier)):[2002ITCAD..21..674N](https://ui.adsabs.harvard.edu/abs/2002ITCAD..21..674N). [doi](/source/Doi_(identifier)):[10.1109/TCAD.2002.1004311](https://doi.org/10.1109%2FTCAD.2002.1004311).

- [SMT-LIB: The Satisfiability Modulo Theories Library](http://smtlib.org/)

- [SMT-COMP: The Satisfiability Modulo Theories Competition](http://www.smtcomp.org)

- [Decision procedures - an algorithmic point of view](http://www.decision-procedures.org:)

- Sebastiani, R. (2007). "Lazy Satisfiability Modulo Theories". *Journal on Satisfiability, Boolean Modeling and Computation*. **3** (3–4): 141–224. [CiteSeerX](/source/CiteSeerX_(identifier)) [10.1.1.100.221](https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.221). [doi](/source/Doi_(identifier)):[10.3233/SAT190034](https://doi.org/10.3233%2FSAT190034).

- This article was originally adapted from a column in the ACM [SIGDA](http://www.sigda.org) [e-newsletter](https://web.archive.org/web/20070208034716/http://www.sigda.org/newsletter/index.html) by [Karem A. Sakallah](/source/Karem_A._Sakallah). The original text is [available here](http://archive.sigda.org/newsletter/2006/061215.txt).

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Adapted from the Wikipedia article [Satisfiability modulo theories](https://en.wikipedia.org/wiki/Satisfiability_modulo_theories) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/Satisfiability_modulo_theories?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.