Overview
========

STP is a constraint solver for the theory of quantifier-free bitvectors
that can solve many kinds of problems generated by program analysis
tools, theorem provers, automated bug finders, cryptographic algorithms,
intelligent fuzzers and model checkers.

A somewhat technical PPT presentation about STP is
`here </images/STP_old_talk.ppt>`__ and a somewhat newer PDF
presentation is `here </images/MIT-vijayganesh-stp-talk.pdf>`__.
Research bibtex reference can be found
`here <http://dblp.uni-trier.de/rec/bibtex/conf/cav/GaneshD07>`__.

.. raw:: html

   <!--The input to STP are formulas over the theory of bitvectors and arrays. This theory captures most expressions from languages like C,C++,Java, Verilog etc. STP can tell if the input formula is satisfiable or not and if is, then it can also generate a variable assignment to satisfy the input formula.-->

Install instructions
====================

For Debian-like platforms first install the prerequisites:

.. code-block:: bash

    apt-get install cmake g++ zlib1g-dev libboost-all-dev flex bison

Then install minisat:

.. code-block:: bash

    git clone https://github.com/stp/minisat.git`
    cd minisat && mkdir build && cd build
    cmake ..
    make
    sudo make install
    cd ../..

Then install STP:

.. code-block:: bash

    git clone https://github.com/stp/stp.git
    cd stp && mkdir build && cd build
    cmake ..
    make
    sudo make install

For windows-like environments: you will need to first install the zlib
library then install minisat and stp exactly like above, using cmake to
create Visual Studio project files, e.g.
``cmake .. -G "Visual Studio 10 Win64"`` and then building with Visual
Studio.


Languages parsed
================

The file based input formats that STP reads are the: CVC, SMT-LIB1, and
SMT-LIB2 formats. The SMT-LIB2 format is the recommended file format,
because it is parsed by all modern bitvector solvers. STP implements a
subset of the SMT-LIB2 language; not all SMT-LIB2 features are
implemented.

.. toctree::
   :maxdepth: 1

   smt-input-language
   cvc-input-language


Python usage
============

.. code-block:: python

    import stp
    s = stp.Solver()
    a = s.bitvec('a', 32)
    b = s.bitvec('b', 32)
    c = s.bitvec('c', 32)
    s.add(a == 5)
    s.add(b == 6)
    s.add(a + b == c)
    s.check()
    >>> True
    s.model()
    >>> {'a': 5L, 'b': 6L, 'c': 11L}

SMT-LIBv2 Usage
===============

Signed division of -1/-2 = 0, should be satisfiable.

.. code-block:: lisp

    (set-logic QF_BV)
    (assert (= (bvsdiv (_ bv3 2) (_ bv2 2)) (_ bv0 2)))
    (check-sat)
    (exit)

C library usage
===============

When STP is built it generates a ``lib/libstp.a`` static library which
can be used with one of two header files, depending on the preferred
language:

-  ``include/stp/c_interface.h`` for a C interface to STP
-  ``include/stp/cpp_interface.h`` for a C++ interface to STP

An example C header usage can be as simple as:

.. code-block:: c

    #include "stp/c_interface.h"
    #include <assert.h>

    int main(int argc, char **argv) {
      VC vc = vc_createValidityChecker();

      // 32-bit variable 'c'
      Expr c = vc_varExpr(vc, "c", vc_bvType(vc, 32));

      // 32 bit constant value 5
      Expr a = vc_bvConstExprFromInt(vc, 32, 5);

      // 32 bit constant value 6
      Expr b = vc_bvConstExprFromInt(vc, 32, 6);

      // a+b!=c
      Expr xp1 = vc_bvPlusExpr(vc, 32, a, b);
      Expr eq = vc_eqExpr(vc, xp1, c);
      Expr eq2 = vc_notExpr(vc, eq);

      //Is a+b!=c always correct?
      int ret = vc_query(vc, eq2);

      //No, c=a+b is a counterexample
      assert(ret == false);

      //print c = 11 counterexample
      vc_printCounterExample(vc);

      //Delete validity checker
      vc_Destroy(vc);

      return 0;
    }

If you use CMake as the build system for your project it is easy to use
STP as an external project. An example can be found in the sources under |examples|_.

.. |examples| replace:: ``examples/simple``
.. _examples: https://github.com/stp/stp/tree/master/examples/simple


Awards
======

-  STP placed `2nd in the bitvector
   category <http://www.msoos.org/2014/06/smt-competition14-and-stp/>`__
   in the SMTCOMP 2014, just after the proprietary
   `Boolector <http://fmv.jku.at/boolector/>`__ system
-  STP placed 2nd in the bitvector category in the SMTCOMP 2011
-  STP won the bitvector category at `SMTCOMP
   2010 <http://www.smtcomp.org/2010/>`__
-  STP won the `SMTCOMP
   2006 <https://www.cs.upc.edu/~oliveras/espai/papers/JAR-smtcomp.pdf>`__
   competition (Bitvector category) in 2006

Use cases
=========

-  `KLEE symbolic fuzzer <http://klee.github.io/>`__ is using STP at its
   core (Professor Cristian Cadar’s group at Imperial College, London,
   and Professor Dawson Engler’s group at Stanford University)
-  `Souper project <https://github.com/google/souper>`__ at the
   University of Utah and Google
-  `S2E <http://s2e.epfl.ch/>`__ at EPFL
-  Mayhem fuzzer, which `found over 1000
   bugs <http://lwn.net/Articles/557055/>`__ in mainline Debian is using
   KLEE and hence STP
-  `Binary Analysis Platform (BAP) <http://bap.ece.cmu.edu/>`__ is using
   STP for analysis, by the CMU
-  `EXE <http://people.csail.mit.edu/vganesh/STP_files/exe.pdf>`__ is a
   symbolic-execution based bug-finding tool that reads your C program
   and tries to automatically crash it (Stanford University)
-  `MINESWEEPER <http://users.ece.cmu.edu/~dawnsong/>`__ is a tool that
   automatically analyzes certain malicious behavior in unix utilities
   and malware. (Carnegie Mellon University)
-  `CATCHCONV <http://sourceforge.net/projects/catchconv/>`__ is a bug
   finding tool that tries to find bugs due to type mismatch in C
   programs. (University of California, Berkeley)
-  Backward path-sensitive analysis of C programs to find bugs by Tim
   Leek from MIT Lincoln Labs
-  Bug finding in Verilog code (a major microprocessor company)
-  `JPF-SE <http://ase.arc.nasa.gov/people/pcorina/papers/jpfseTACAS07.pdf>`__
   is a symbolic execution extension to the Java PathFinder model
   checker . (NASA Ames Research Center)
-  `Avalanche <http://code.google.com/p/avalanche/>`__ bug-finding tool
   (Institute of Systems Programming, Moscow, Russia)
-  `Low-level Bounded Model Checker - LLBMC <http://llbmc.org/>`__
   (Karlsruhe Institute of Technology (KIT), Germany)
-  `FuzzGrind <http://esec-lab.sogeti.com/pages/Fuzzgrind>`__ (ESEC Lab)
-  In conjunction with
   `ACL2 <http://www.cs.utexas.edu/users/moore/acl2/>`__ to formally
   verify implementation of encryption algorithms in Java (Stanford
   University)
-  `Hampi <http://people.csail.mit.edu/akiezun/hampi/>`__ : A solver for
   string constraints used to automatically construct SQL injection and
   XSS exploits (MIT)
-  Automatic configuration: Tvl2STP (University of Namur in Belgium)

Architecture
============

STP is an efficient decision procedure for the validity (or
satisfiability) of formulas from a quantifier-free many-sorted theory of
fixed-width bitvectors and (non-extensional) one-dimensional arrays. The
functions in STP’s input language include concatenation, extraction,
left/right shift, sign-extension, unary minus, addition, multiplication,
(signed) modulo/division, bitwise Boolean operations, if-then-else
terms, and array reads and writes. The predicates in the language
include equality and (signed) comparators between bitvector terms.

The basic architecture of STP essentially follows the idea of word-level
preprocessing followed by translation to SAT (We use MINISAT and
CRYPTOMINISAT). In particular, we introduce several new heuristics for
the preprocessing step, including abstraction-refinement in the context
of arrays, a new bitvector linear arithmetic equation solver, and some
interesting simplifications. These heuristics help us achieve several
magnitudes of order performance over other tools, and also over
straight-forward translation to SAT. STP has been heavily tested on
thousands of examples sourced from various real-world applications such
as program analysis and bug-finding tools like EXE, and equivalence
checking tools and theorem-provers.

History and authors
===================

The initial versions of STP were written primarily by Vijay Ganesh as
part of his PhD thesis, and the project was later maintained by Trevor
Hansen. The current primary maintainers are Mate Soos, Dan Liew, and
Ryan Govostes who have improved it in many ways. STP is based on the
following papers:

-  `A Decision Procedure for Bit-Vectors and
   Arrays <https://ece.uwaterloo.ca/~vganesh/Publications_files/vg2007-STP-CAV.pdf>`__
   by Vijay Ganesh and David L. Dill. In Proceedings of the
   International Conference in Computer Aided Verification (CAV 2007),
   Berlin, Germany, July 2007

-  `EXE: Automatically Generating Inputs of
   Death <https://ece.uwaterloo.ca/~vganesh/Publications_files/vg2006-EXE-CCS.pdf>`__
   by Cristian Cadar, Vijay Ganesh, Peter Pawlowski, Dawson Engler,
   David Dill. In Proceedings of ACM Conference on Computer and
   Communications Security 2006 (CCS 2006), Alexandria, Virginia,
   October, 2006

Past contributors: Khoo Yit Phang, Ed Schwartz, Mike Katelman (PhD
Student, University of Illinois, Urbana-Champaign, IL, USA), Philip Guo
(Student, Stanford University, Stanford, CA, USA), David L. Dill
(Professor, Stanford University, Stanford, CA, USA), Tim King (Student,
Stanford University and NYU). Please note that everyone working on the
project is doing so out of hobby or as a way to help them in their
work/study projects.
