#problem #interface #sat-solver #boolean #satisfiability #forms #normal

minisat

MiniSat Rust interface. Solves a boolean satisfiability problem given in conjunctive normal form.

14 releases

Uses old Rust 2015

0.4.4 Nov 17, 2019
0.4.3 Apr 24, 2019
0.4.2 Jan 29, 2019
0.4.0 Nov 22, 2018
0.1.1 Oct 21, 2018

#1968 in Algorithms

23 downloads per month
Used in rust-formal-verification

MIT license

360KB
6.5K SLoC

C++ 5K SLoC // 0.2% comments Rust 1.5K SLoC // 0.0% comments

MiniSat Rust interface. Solves a boolean satisfiability problem given in conjunctive normal form.

extern crate minisat;
use std::iter::once;
fn main() {
    let mut sat = minisat::Solver::new();
    let a = sat.new_lit();
    let b = sat.new_lit();

    // Solves ((a OR not b) AND b)
    sat.add_clause(vec![a, !b]);
    sat.add_clause(vec![b]);

    match sat.solve() {
        Ok(m) => {
            assert_eq!(m.value(&a), true);
            assert_eq!(m.value(&b), true);
        },
        Err(()) => panic!("UNSAT"),
    }
}

This crate compiles the MiniSat sources directly and binds through the minisat-c-bindings interface. The low-level C bindings are available through the sys module.

High-level features ported from satplus:

  • Traits for representing non-boolean values in the SAT problem:
    • Value trait (ModelValue)
    • Equality trait (ModelEq)
    • Ordering trait (ModelOrd)
  • Symbolic values (Symbolic<V>)
  • Non-negative integers with unary encoding (Unary)
  • Non-negative integers with binary encoding (Binary)

Graph coloring example:

extern crate minisat;
use std::iter::once;
use minisat::symbolic::*;
fn main() {
    let mut coloring = minisat::Solver::new();

    #[derive(PartialEq, Eq, Debug, PartialOrd, Ord)]
    enum Color { Red, Green, Blue };

    let n_nodes = 5;
    let edges = vec![(0,1),(1,2),(2,3),(3,4),(3,1),(4,0),(4,2)];
    let colors = (0..n_nodes)
        .map(|_| Symbolic::new(&mut coloring, vec![Color::Red, Color::Green, Color::Blue]))
        .collect::<Vec<_>>();
    for (n1,n2) in edges {
        coloring.not_equal(&colors[n1],&colors[n2]);
    }
    match coloring.solve() {
        Ok(model) => {
            for i in 0..n_nodes {
                println!("Node {}: {:?}", i, model.value(&colors[i]));
            }
        },
        Err(()) => {
            println!("No solution.");
        }
    }
}

Factorization example:

extern crate minisat;
use minisat::{*, binary::*};

fn main() {
    let mut sat = Solver::new();
    let a = Binary::new(&mut sat, 1000);
    let b = Binary::new(&mut sat, 1000);
    let c = a.mul(&mut sat, &b);
    sat.equal(&c, &Binary::constant(36863));

    match sat.solve() {
        Ok(model) => {
            println!("{}*{}=36863", model.value(&a), model.value(&b));
        },
        Err(()) => {
            println!("No solution.");
        }
    }
}

Sudoku solver, based on the article Modern SAT solvers: fast, neat and underused (part 1 of N). It uses the sudoku crate for generating and displaying boards.

extern crate itertools;
extern crate sudoku;
use itertools::iproduct;
use minisat::Solver;
use minisat::symbolic::Symbolic;
use sudoku::Sudoku;

pub fn solve_sudoku(problem: &str) -> Option<String> {
    let mut s = Solver::new();
    let matrix = problem.chars().map(|c| {
        if let Some(i) = c.to_digit(10) {
            Symbolic::new(&mut s, vec![i - 1])
        } else {
            Symbolic::new(&mut s, (0..9).collect())
        }
    }).collect::<Vec<_>>();

    for val in 0..9 {
        // Rule 1: no row contains duplicate numbers
        for x in 0..9 {
            s.assert_at_most_one((0..9).map(|y| matrix[9 * y + x].has_value(&val)));
        }
        // Rule 2: no column contains duplicate numbers
        for y in 0..9 {
            s.assert_at_most_one((0..9).map(|x| matrix[9 * y + x].has_value(&val)));
        }
        // Rule 3: no 3x3 box contains duplicate numbers
        for (box_x, box_y) in iproduct!((0..9).step_by(3), (0..9).step_by(3)) {
            s.assert_at_most_one(
                iproduct!(0..3, 0..3)
                    .map(|(x, y)| matrix[9 * (box_x + x) + (box_y + y)].has_value(&val)),
            );
        }
    }

    s.solve().ok().map(|m| {
        matrix.into_iter()
            .map(|v| format!("{}", m.value(&v) + 1))
            .collect()
    })
}



fn main() {
    let puzzle = Sudoku::generate_unique();
    println!("{}", puzzle.display_block());

    let solution = solve_sudoku(&puzzle.to_str_line()).expect("Unable to solve puzzle");
    let solved_puzzle = Sudoku::from_str_line(&solution).expect("Unable to parse puzzle");

    println!("{}", solved_puzzle.display_block());
    assert!(solved_puzzle.is_solved());
}

Dependencies

~0.4–2.4MB
~46K SLoC