Counter-example guided inductive synthesis (CEGIS) implementation for the SMT solver Z3 by Microsoft Research. CEGIS is an approach to tackle complexity of exact syntheses using satisfiability solvers. It was first introduced by Armando Solar-Lezama in his Ph.D. Thesis Program Synthesis by Sketching back in 2008.

Synthesis tasks often have the same structure: an implementation is sought that behaves correctly under all possible inputs (with the help of some extra variables, i.e. helper variables).

More formal: ∃ Implementation : ∀ Inputs : ∃ Helper Variables : Implementation behaves correctly.

It is absolutely legal to pass such a term to an SMT solver like Z3. A big drawback is the universal quantifier though.

For many real world problems it is not necessary to consider all inputs to derive an implementation that behaves correctly for all of them. Following this observation, the problem was just moved to another position: which is the minimal subset of inputs one have to consider to ensure a correct synthesis?

This is the point where CEGIS comes into play. CEGIS is a loop looking for exactly this minimal subset of inputs and performing the implementation synthesis as a "by-product". Therefore CEGIS uses one satisfiability solver to generate new implementations based on all the inputs considered so far (starting with zero); and another one to generate counter examples that uncover incorrect behavior in the latest synthesised implementation. Eventually there will be no more implementations possible, i.e. the specification is not realisable, or no more counter examples possible, i.e. the latest implementation must be correct.

This CEGIS library works with the SMT solver Z3 and requires insight in the synthesis task to be executed, as it has to be specified which variables belong to implementation, inputs, etc. Boundary conditions are to be specified manually as well.

Git, g++, cmake, a Python interpreter and the Boost Library are necessary in order to build CEGIS. In Ubuntu the packages can be installed with

sudo apt-get install git g++ cmake python libboost-all-dev

Afterwards, CEGIS is ready to be installed.

git clone https://github.com/marcelwa/CEGIS.git
cd CEGIS
mkdir build
cd build
cmake ..
make
sudo make install

Since Z3 is automatically downloaded, configured and installed during this procedure, this step may take a while. Please enter your super user password to provide installation rights.

The standard install prefix is /usr/local/. If another prefix is desired, just replace cmake .. by cmake -DCMAKE_INSTALL_PREFIX:PATH=/YOUR_PREFIX ... If you do not want Z3 to be downloaded and installed during the build step because you have it already set up in your system, simply add -DINSTALL_Z3=OFF to your cmake parameter list. Both options can be configured using ccmake, too, of course.

If you want to uninstall the CEGIS library and the downloaded Z3 solver, simply type

sudo xargs rm < install_manifest.txt

in the build directory.

The functionality of this library is encapsulated in a class called CEGISHandler. This class handles the given variables, constraints and execution of the CEGIS loop as well as runtime measurement and many other tasks.

using namespace z3;

/* PREVIOUS USAGE */
context c;

// ...a lot of stuff...
 
solver s(c);
s.add(exists(implementation, forall(inputs, exists(helpers, constraints))));
s.check();


/* BETTER CEGIS USAGE */
context c;

// implementation, input and helper variables
expr_vector impl(c), inp(c), hlp(c);

// ...fill the vectors...

// implementation constraints, e.g. no cycles allowed
expr impl_cons(c);
// behavior constraints, e.g. desired propagation
expr behav_cons(c);
// correctness constraints, e.g. outputs depend on the inputs in a specifc way
expr corr_cons(c);

// ...fill all those...

// let's rock CEGIS
CEGISHandler handler(&c, impl, inp, hlp, impl_cons, behav_cons, corr_cons);
auto result = handler.CEGISRoutine();
result.print();