d2b618df23
* Make spacer_sem_matcher::reset() public * Add .clang-format for src/muz/spacer * Mark substitution::get_bindings() as const * Fix in spacer_antiunify * Various helper methods in spacer_util Minor functions to compute number of free variables, detect presence of certain sub-expressions, etc. The diff is ugly because of clang-format * Add spacer_cluster for clustering lemmas A cluster of lemmas is a set of lemmas that are all instances of the same pattern, where a pattern is a qff formula with free variables. Currently, the instances are required to be explicit, that is, they are all obtained by substituting concrete values (i.e., numbers) for free variables of the pattern. Lemmas are clustered in cluster_db in each predicate transformer. * Integrate spacer_cluster into spacer_context * Custom clang-format pragmas for spacer_context spacer_context.(cpp|h) are large and have inconsistent formatting. Disable clang-format for them until merge with main z3 branch and re-format. * Computation of convex closure and matrix kernel Various LA functions. The implementations are somewhat preliminary. Convex closure is simplemented via syntactic convex closure procedure. Kernel computation considers many common cases. spacer_arith_kernel_sage implements kernel computation by call external Sage binary. It is used only for debugging and experiments. There is no link dependence on Sage. If desired, it can be removed. * Add spacer_concretize * Utility methods for spacer conjecture rule * Add spacer_expand_bnd_generalizer Generalizes arithmetic inequality literals of the form x <= c, by changing constant c to other constants found in the problem. * Add spacer_global_generalizer Global generalizer checks every new lemma against a cluster of previously learned lemmas, and, if possible, conjectures a new pob, that, when blocked, generalizes multiple existing lemmas. * Remove fp.spacer.print_json option The option is used to dump state of spacer into json for debugging. It has been replaced by `fp.spacer.trace_file` that allows dumping an execution of spacer. The json file can be reconstructed from the trace file elsewhere. * Workaround for segfault in spacer_proof_utils Issue #3 in hgvk94/z3 Segfault in some proof reduction. Avoid by bailing out on reduction. * Revert bug for incomplete models * Use local fresh variables in spacer_global_generalizer * Cleanup of spacer_convex_closure * Allow arbitrary expressions to name cols in convex_closure * WIP: convex closure * WIP: convex closure * Fix bindings order in spacer_global_generalizer The matcher creates substitution using std_order, which is reverse of expected order (variable 0 is last). Adjust the code appropriately for that. * Increase verbosity level for smt_context stats * Dead code in qe_mbp * bug fixes in spacer_global_generalizer::subsumer * Partially remove dependence of size of m_alphas I want m_alphas to potentially be greater than currently used alpha variables. This is helpful for reusing them across multiple calls to convex closure * Subtle bug in kernel computation Coefficient was being passed by reference and, therefore, was being changed indirectly. In the process, updated the code to be more generic to avoid rational computation in the middle of matrix manipulation. * another test for sparse_matrix_ops::kernel * Implementation of matrix kernel using Fraction Free Elimination Ensures that the kernel is int for int matrices. All divisions are exact. * clang-format sparse_matrix_ops.h * another implementation of ffe kernel in sparse_matrix_ops * Re-do arith_kernel and convex_closure * update spacer_global_generalization for new subsumer * remove spacer.gg.use_sage parameter * cleanup of spacer_global_generalizer * Removed dependency on sage * fix in spacer_convex_closure * spacer_sem_matcher: consider an additional semantic matching disabled until it is shown useful * spacer_global_generalizer: improve do_conjecture - if conjecture does not apply to pob, use lemma instead - better normalization - improve debug prints * spacer_conjecture: formatting * spacer_cluster: improve debug prints * spacer_context: improve debug prints * spacer_context: re-queue may pobs enabled even if global re-queue is disabled * spacer_cluster print formatting * reset methods on pob * cleanup of print and local variable names * formatting * reset generalization data once it has been used * refactored extra pob creation during global guidance * fix bug copying sparse matrix into spacer matrix * bug fix in spacer_convex_closure * formatting change in spacer_context * spacer_cluster: get_min_lvl chose level based on pob as well as lemmas * spacer_context: add desired_level to pob desired_level indicates at which level pob should be proved. A pob will be pushed to desired_level if necessary * spacer_context: renamed subsume stats the name of success/failed was switched * spacer_convex_closure: fix prototype of is_congruent_mod() * spacer_convex_closure: hacks in infer_div_pred() * spacer_util: do not expand literals with mod By default, equality literal t=p is expanded into t<=p && t>=p Disable the expansion in case t contains 'mod' operator since such expansion is usually not helpful for divisibility * spacer_util: rename m_util into m_arith * spacer_util: cleanup normalize() * spacer_util: formatting * spacer_context: formatting cleanup on subsume and conjecture * spacer_context: fix handling may pobs when abs_weakness is enabled A pob might be undef, so weakness must be bumped up * spacer_arith_kernel: enhance debug print * spacer_global_generalizer: improve matching on conjecture * spacer_global_generalizer: set desired level on conjecture pob * spacer_global_generalizer: debug print * spacer_global_generalizer: set min level on new pobs the new level should not be higher than the pob that was generalized * spacer_global_generalizer: do no re-create closed pobs If a generalized pob exist and closed, do not re-create it. * spacer_context: normalize twice * spacer_context: forward propagate only same kind of pobs * sketch of inductive generalizer A better implementation of inductive generalizer that in addition to dropping literals also attempts to weaken them. Current implementation is a sketch to be extended based on examples/requirements. * fix ordering in spacer_cluster_util * fix resetting of substitution matcher in spacer_conjecture Old code would forget to reset the substitution provided to the sem_matcher. Thus, if the substitution was matched once (i.e., one literal of interest is found), no other literal would be matched. * add spacer_util is_normalized() method used for debugging only * simplify normalization of pob expressions pob expressions are normalized to increase syntactic matching. Some of the normalization rules seem out of place, so removing them for now. * fix in spacer_global_generalizer If conjecture fails, do not try other generalization strategies -- they will not apply. * fix in spacer_context do not check that may pob is blocked by existing lemmas. It is likely to be blocked. Our goal is to block it again and generalize to a new lemma. This can be further improved by moving directly to generalization when pob is blocked by existing lemmas... Co-authored-by: hgvk94 <hgvk94@gmail.com> |
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| .github | ||
| cmake | ||
| contrib | ||
| doc | ||
| docker | ||
| examples | ||
| noarch | ||
| resources | ||
| scripts | ||
| src | ||
| .dockerignore | ||
| .gitattributes | ||
| .gitignore | ||
| azure-pipelines.yml | ||
| CMakeLists.txt | ||
| configure | ||
| LICENSE.txt | ||
| package-lock.json | ||
| Parameters.md | ||
| README-CMake.md | ||
| README.md | ||
| RELEASE_NOTES.md | ||
| z3.pc.cmake.in | ||
Z3
Z3 is a theorem prover from Microsoft Research. It is licensed under the MIT license.
If you are not familiar with Z3, you can start here.
Pre-built binaries for stable and nightly releases are available from here.
Z3 can be built using Visual Studio, a Makefile or using CMake. It provides bindings for several programming languages.
See the release notes for notes on various stable releases of Z3.
Build status
| Azure Pipelines | Code Coverage | Open Bugs | Android Build | WASM Build |
|---|---|---|---|---|
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Building Z3 on Windows using Visual Studio Command Prompt
32-bit builds, start with:
python scripts/mk_make.py
or instead, for a 64-bit build:
python scripts/mk_make.py -x
then:
cd build
nmake
Z3 uses C++17. The recommended version of Visual Studio is therefore VS2019.
Building Z3 using make and GCC/Clang
Execute:
python scripts/mk_make.py
cd build
make
sudo make install
Note by default g++ is used as the C++ compiler if it is available. If you
would prefer to use Clang change the mk_make.py invocation to:
CXX=clang++ CC=clang python scripts/mk_make.py
Note that Clang < 3.7 does not support OpenMP.
You can also build Z3 for Windows using Cygwin and the Mingw-w64 cross-compiler. To configure that case correctly, make sure to use Cygwin's own python and not some Windows installation of Python.
For a 64 bit build (from Cygwin64), configure Z3's sources with
CXX=x86_64-w64-mingw32-g++ CC=x86_64-w64-mingw32-gcc AR=x86_64-w64-mingw32-ar python scripts/mk_make.py
A 32 bit build should work similarly (but is untested); the same is true for 32/64 bit builds from within Cygwin32.
By default, it will install z3 executable at PREFIX/bin, libraries at
PREFIX/lib, and include files at PREFIX/include, where PREFIX
installation prefix is inferred by the mk_make.py script. It is usually
/usr for most Linux distros, and /usr/local for FreeBSD and macOS. Use
the --prefix= command line option to change the install prefix. For example:
python scripts/mk_make.py --prefix=/home/leo
cd build
make
make install
To uninstall Z3, use
sudo make uninstall
To clean Z3 you can delete the build directory and run the mk_make.py script again.
Building Z3 using CMake
Z3 has a build system using CMake. Read the README-CMake.md file for details. It is recommended for most build tasks, except for building OCaml bindings.
Dependencies
Z3 itself has few dependencies. It uses C++ runtime libraries, including pthreads for multi-threading. It is optionally possible to use GMP for multi-precision integers, but Z3 contains its own self-contained multi-precision functionality. Python is required to build Z3. To build Java, .Net, OCaml, Julia APIs requires installing relevant tool chains.
Z3 bindings
Z3 has bindings for various programming languages.
.NET
You can install a nuget package for the latest release Z3 from nuget.org.
Use the --dotnet command line flag with mk_make.py to enable building these.
See examples/dotnet for examples.
C
These are always enabled.
See examples/c for examples.
C++
These are always enabled.
See examples/c++ for examples.
Java
Use the --java command line flag with mk_make.py to enable building these.
See examples/java for examples.
OCaml
Use the --ml command line flag with mk_make.py to enable building these.
See examples/ml for examples.
Python
You can install the Python wrapper for Z3 for the latest release from pypi using the command
pip install z3-solver
Use the --python command line flag with mk_make.py to enable building these.
Note that it is required on certain platforms that the Python package directory
(site-packages on most distributions and dist-packages on Debian based
distributions) live under the install prefix. If you use a non standard prefix
you can use the --pypkgdir option to change the Python package directory
used for installation. For example:
python scripts/mk_make.py --prefix=/home/leo --python --pypkgdir=/home/leo/lib/python-2.7/site-packages
If you do need to install to a non standard prefix a better approach is to use
a Python virtual environment
and install Z3 there. Python packages also work for Python3.
Under Windows, recall to build inside the Visual C++ native command build environment.
Note that the build/python/z3 directory should be accessible from where python is used with Z3
and it depends on libz3.dll to be in the path.
virtualenv venv
source venv/bin/activate
python scripts/mk_make.py --python
cd build
make
make install
# You will find Z3 and the Python bindings installed in the virtual environment
venv/bin/z3 -h
...
python -c 'import z3; print(z3.get_version_string())'
...
See examples/python for examples.
Julia
The Julia package Z3.jl wraps the C++ API of Z3. Information about updating and building the Julia bindings can be found in src/api/julia.
Web Assembly / TypeScript / JavaScript
A WebAssembly build with associated TypeScript typings is published on npm as z3-solver. Information about building these bindings can be found in src/api/js.
Smalltalk (Pharo / Smalltalk/X)
Project MachineArithmetic provides Smalltalk interface to Z3's C API. For more information, see MachineArithmetic/README.md
System Overview
Interfaces
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Default input format is SMTLIB2
-
Other native foreign function interfaces:
-
Python API (also available in pydoc format)
-
C
-
OCaml
-
Smalltalk (supports Pharo and Smalltalk/X)