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I have been working on other projects recently and haven't had the stamina to keep things up to date. I may take up maintainership again in the future.

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XSat is a fast floating-point constraint solver. Evaluated on 34 representative SMT Competition benchmarks, XSat provides consistent satisfiability results as MathSat and Z3, and an average of more than 700X performance speedup.

DISCLAIMER: XSat currently does not supports all QF_FP operations. This version supports the arithmetic operations of the QF_FP (Quantifier-Free Floating-Point) theory, including: fp.leq, fp.lt, fp.geq, fp.gt, fp.eq, fp.neg, fp.add, fp.mult, fp.sub and fp.div.

See Fu and Su's CAV'16 paper for the algorithm and implementation details.

Dependencies

  • python 2.7
  • python packages: python-dev, sympy, numpy, scipy
  • Clang (preferred, which allows you to use the -fbracket-depth option, see below), or gcc
  • Z3 (I used its 4.5.0 version for parsing SMT2 files)

Running XSat

Note:

  1. To resolve runtime dependencies, you probably need to set environment variables (such as LD_LIBRARY_PATH or PYTHONPATH) or variables defined in Makefile.

  2. The option "-fbracket-depth" is from Clang. Gcc does not have that option. The option is to deal with situations where the generated C file gets many brackets. You can disable that option in Makefile and you should be fine most of the time. Meanwhile, I plan to optimize a bit the algorithm (there is large room!) to avoid generating too many brackets, so hopefully, that option can be safely removed in the future.

Running from the source

Consider a benchmark constraint located at Benchmarks/div3.c.50.smt2. The first command below compiles the constraint into a C shared object. The second command below invokes an external stochastic optimization backend to solve the constraint.

$ make IN=Benchmarks/div3.c.50.smt2
$ python xsat.py 

You can type make helloworld as a shortcut.

Note: the second command above can be supplemented with a range of options. Use "--help" to get the list of command line options. In particular, the "--debug" option is set on by default, meaning that you will see verbose output. To get only the satisfiability result, supplement the second command with "--bench" option.

Running from the docker

Note: The docker is provided for your convenience, but code maintenance is only on the source.

First, get the image and start the container:

docker pull martinvelez/xsat
docker run -it martinvelez/xsat:latest bash

Then, run XSat from the source.

Testing XSat

$ python test_benchmarks.py 

This command tests XSat on a suite of the 34 benchmarks used in the paper, table 1. To test only a subset of these benchmarks, use python test_benchmarks.py --quick <n> where n is a positive integer. With n = 10, the command tests the 10th, 20th and 30th benchmark of the suite.

Expected results

$ time python test_benchmarks.py
(1) Working on Benchmarks/div2.c.30.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(2) Working on Benchmarks/mult1.c.30.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
...
...
(28) Working on Benchmarks/test_v5_r10_vr10_c1_s21502.smt2
   Compiling ...
   Solving ...
   ==> unsat [Expected]
(29) Working on Benchmarks/sin2.c.10.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(30) Working on Benchmarks/div2.c.50.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(31) Working on Benchmarks/mult1.c.50.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(32) Working on Benchmarks/div3.c.50.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(33) Working on Benchmarks/mult2.c.50.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]
(34) Working on Benchmarks/div.c.50.smt2
   Compiling ...
   Solving ...
   ==> sat [Expected]

real	1m53.170s
user	4m55.804s
sys	    0m24.029s

I recently found that XSat sometimes gave incorrect results for sin2.c.10.smt2 (#29 above). It can be a new bug, or week parameter settings (e.g. insufficient iteration numbers), but I do not have time to investigate on this at this moment.

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A Fast Floating-Point Satisfiability Solver

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