libdlx is a C implementation of dancing links, an efficient backtracking algorithm that solves
instances of the Exact Cover problem. For more information on the Exact Cover problem see the
paper in libdlx/doc/
or visit wikipedia
This project includes two non-trivial example programs that use libdlx: sudgen and sudslv. sudgen is a sudoku puzzle generator, sudslv is a sudoku puzzle solver.
$ make
The build will produce these artifacts:
libdlx
(both a static and a dynamic library)sudgen
(sudoku puzzle generator)sudslv
(sudoku puzzle solver)
Cross compile to js using $ make js
(you need to have Emscripten installed).
Run afterwards using $ node build-js/bin/sudgen.js
Run $ make test
after building or try the below command (your output will differ, puzzle is randomly generated):
$ pushd build && ./bin/sudgen | tee >(./bin/sudslv) | ../sudoku/pretty-print-puzzle.py && popd
+---+---+---+
|5 3| |8 7|
| | | |
| | 76|4 |
+---+---+---+
|1 | 3 | |
| |9 5| 1|
| 2| 4 | |
+---+---+---+
|74 | |3 |
| 5 | 1| 6 |
| 8| | 2 |
+---+---+---+
+---+---+---+
|563|412|897|
|427|893|156|
|981|576|432|
+---+---+---+
|175|638|249|
|834|925|671|
|692|147|583|
+---+---+---+
|746|259|318|
|259|381|764|
|318|764|925|
+---+---+---+
Tested under:
- OSX 10.11 using clang 7.0.0
- FreeBSD 9.3 using cc 4.2.1
-
libdlx/
C library, implementation of dancing links
-
sudoku/sudgen/
Sudoku generator. Outputs a single puzzle to stdout.
Properties of generated puzzles:
- there is a unique solution
- puzzle is minimal, that is to say that removing any given would render it non-unique
-
sudoku/sudslv/
Reads sudoku puzzles (1 per line) from stdin until EOF and:
- outputs their solution as a single line if there is one
- reports to stderr if the puzzle has 0 or more than 1 solution
-
pydlx/
Python bindings, these are needed for running the unit tests and most of the examples.
None except the C standard library.
Note: you do need python to run the tests and most of the examples.
A simple example of how to use libdlx
can be found in examples/example-2x2-matrix.c
.
In addition, the examples directory contains scripts to generate instances to Exact Cover with, these include:
-
examples/generate-nxn-latin-square-matrix.py n
count latin squares of size
n
-
examples/generate-n-queens-matrix.py n
solving the
n
-queens problem (n=19 took about 3.5hrs) -
examples/generate-nxn-sudoku-matrix.py n
counting sudoku grids with boxes of size
n
To solve the 8-queens problem you'd run this:
$ cd examples
$ ./generate-n-queens-matrix.py 8 | ./count-solutions.py
92
The implementation is pretty speedy:
$ time xz -dc sudoku/sudoku17.txt.xz | ./build/bin/sudslv > /dev/null
xz -dc sudoku/sudoku17.txt.xz 0.04s user 0.01s system 1% cpu 2.821 total
./build/bin/sudslv > /dev/null 2.87s user 0.00s system 99% cpu 2.880 total
$ xz -dc sudoku/sudoku17.txt.xz | wc -l
49151 data/sudoku17.txt
sudslv
can solve about 17,125 puzzles/sec/core on a 3.5 GHz Intel Core i5