Sage supports solving clauses in Conjunctive Normal Form (see Wikipedia article Conjunctive_normal_form), i.e., SAT solving, via an interface inspired by the usual DIMACS format used in SAT solving [SG09]. For example, to express that:

```
x1 OR x2 OR (NOT x3)
```

should be true, we write:

```
(1, 2, -3)
```

Warning

Variable indices **must** start at one.

Any SAT solver supporting the DIMACS input format is easily interfaced using the
`sage.sat.solvers.dimacs.DIMACS` blueprint. Sage ships with pre-written interfaces for *RSat*
[RS] and *Glucose* [GL]. Furthermore, Sage provides a C++ interface to the *CryptoMiniSat* [CMS] SAT
solver which can be used interchangably with DIMACS-based solvers, but also provides advanced
features. For this, the optional CryptoMiniSat package must be installed, this can be accomplished
by typing:

```
sage: install_package('cryptominisat') # not tested
```

and by running `sage -b` from the shell afterwards to build Sage’s CryptoMiniSat extension module.

Since by default Sage does not include any SAT solver, we demonstrate key features by instantiating a fake DIMACS-based solver. We start with a trivial example:

```
(x1 OR x2 OR x3) AND (x1 OR x2 OR (NOT x3))
```

In Sage’s notation:

```
sage: from sage.sat.solvers.dimacs import DIMACS
sage: solver = DIMACS(command="sat-solver")
sage: solver.add_clause( ( 1, 2, 3) )
sage: solver.add_clause( ( 1, 2, -3) )
```

Note

`sage.sat.solvers.dimacs.DIMACS.add_clause()` creates new variables when necessary. In
particular, it creates *all* variables up to the given index. Hence, adding a literal involving
the variable 1000 creates up to 1000 internal variables.

DIMACS-base solvers can also be used to write DIMACS files:

```
sage: from sage.sat.solvers.dimacs import DIMACS
sage: fn = tmp_filename()
sage: solver = DIMACS(filename=fn)
sage: solver.add_clause( ( 1, 2, 3) )
sage: solver.add_clause( ( 1, 2, -3) )
sage: _ = solver.write()
sage: for line in open(fn).readlines():
....: print line,
p cnf 3 2
1 2 3 0
1 2 -3 0
```

Alternatively, there is `sage.sat.solvers.dimacs.DIMACS.clauses()`:

```
sage: from sage.sat.solvers.dimacs import DIMACS
sage: fn = tmp_filename()
sage: solver = DIMACS()
sage: solver.add_clause( ( 1, 2, 3) )
sage: solver.add_clause( ( 1, 2, -3) )
sage: solver.clauses(fn)
sage: for line in open(fn).readlines():
....: print line,
p cnf 3 2
1 2 3 0
1 2 -3 0
```

These files can then be passed external SAT solvers.

We demonstrate solving using CryptoMiniSat:

```
sage: from sage.sat.solvers import CryptoMiniSat # optional - cryptominisat
sage: cms = CryptoMiniSat() # optional - cryptominisat
sage: cms.add_clause((1,2,-3)) # optional - cryptominisat
sage: cms() # optional - cryptominisat
(None, True, True, False)
```

Sage supports conversion from Boolean polynomials (also known as Algebraic Normal Form) to Conjunctive Normal Form:

```
sage: B.<a,b,c> = BooleanPolynomialRing()
sage: from sage.sat.converters.polybori import CNFEncoder
sage: from sage.sat.solvers.dimacs import DIMACS
sage: fn = tmp_filename()
sage: solver = DIMACS(filename=fn)
sage: e = CNFEncoder(solver, B)
sage: e.clauses_sparse(a*b + a + 1)
sage: _ = solver.write()
sage: print open(fn).read()
p cnf 3 2
1 0
-2 0
```

Sage provides various highlevel functions which make working with Boolean polynomials easier. We construct a very small-scale AES system of equations and pass it to a SAT solver:

```
sage: sr = mq.SR(1,1,1,4,gf2=True,polybori=True)
sage: F,s = sr.polynomial_system()
sage: from sage.sat.boolean_polynomials import solve as solve_sat # optional - cryptominisat
sage: s = solve_sat(F) # optional - cryptominisat
sage: F.subs(s[0]) # optional - cryptominisat
Polynomial Sequence with 36 Polynomials in 0 Variables
```

REFERENCES:

[RS] | http://reasoning.cs.ucla.edu/rsat/ |

[GL] | http://www.lri.fr/~simon/?page=glucose |

[CMS] | http://www.msoos.org/cryptominisat2/ |

[SG09] | http://www.satcompetition.org/2009/format-benchmarks2009.html |